{ "classifiers" : [ { "candidates" : [ { "acceptedForAutomaticRouting" : true, "algorithm" : "maxEnt", "balancedTrainingCount" : 5760, "balancedValidationCount" : 1440, "binaryByLanguage" : { "en" : { "accuracy" : 0.8839, "f1" : 0.7107, "falseNegative" : 161, "falsePositive" : 1, "precision" : 0.995, "recall" : 0.5528, "total" : 1395, "trueNegative" : 1034, "truePositive" : 199 }, "zh-Hans" : { "accuracy" : 0.9563, "f1" : 0.9074, "falseNegative" : 61, "falsePositive" : 0, "precision" : 1, "recall" : 0.8306, "total" : 1395, "trueNegative" : 1035, "truePositive" : 299 } }, "confidenceThresholdsByLanguage" : { "en" : 0.91, "zh-Hans" : 0.89 }, "goldenBinary" : { "accuracy" : 0.9292, "f1" : 0.6341, "falseNegative" : 15, "falsePositive" : 0, "precision" : 1, "recall" : 0.4643, "total" : 212, "trueNegative" : 184, "truePositive" : 13 }, "goldenBinaryByLanguage" : { "en" : { "accuracy" : 0.934, "f1" : 0.6667, "falseNegative" : 7, "falsePositive" : 0, "precision" : 1, "recall" : 0.5, "total" : 106, "trueNegative" : 92, "truePositive" : 7 }, "zh-Hans" : { "accuracy" : 0.9245, "f1" : 0.6, "falseNegative" : 8, "falsePositive" : 0, "precision" : 1, "recall" : 0.4286, "total" : 106, "trueNegative" : 92, "truePositive" : 6 } }, "goldenFalseNegativeExamples" : [ "[en] Alex owns the meeting notes and should post them in the project channel today. (score=0.8878)", "[en] Could these documents be ready by the end of the month? (score=0.9042)", "[en] Do not forget to check whether the refund arrives on Friday. (score=0.9049)", "[en] After the meeting, summarize the three decisions in the project channel. (score=0.7419)", "[en] When approval arrives, contact the applicant and explain the reason. (score=0.621)", "[en] Follow up with the vendor about the delivery date next Monday. (score=0.8885)", "[en] Next action: create the release tag after the tests pass. (score=0.4708)", "[zh-Hans] 小王负责整理会议纪要，今天发到项目群。 (score=0.4243)", "[zh-Hans] 方便帮我约一下周三下午的会议室吗？ (score=0.1551)", "[zh-Hans] 这些材料可以在月底前准备好吗？ (score=0.6415)", "[zh-Hans] 别忘了周五检查退款有没有到账。 (score=0.6693)", "[zh-Hans] 会后需要整理三个决定并发到项目群。 (score=0.1071)" ], "goldenFalsePositiveExamples" : [ ], "modelBytes" : 27115, "runtimeAssetIndependent" : true, "testBinary" : { "accuracy" : 0.9201, "f1" : 0.8171, "falseNegative" : 222, "falsePositive" : 1, "precision" : 0.998, "recall" : 0.6917, "total" : 2790, "trueNegative" : 2069, "truePositive" : 498 }, "testFalseNegativeExamples" : [ "[en] Also, Reminder: call the client back before the next meeting. (score=0.7075)", "[en] One more thing: Reminder: book the follow-up visit by Friday. (score=0.7023)", "[en] Reminder: check the invoice status by the end of the month. (score=0.8633)", "[en] Reminder: call the client back by the end of the month. (score=0.8156)", "[en] A quick note: Reminder: call the client back before the end of today. (score=0.7158)", "[en] One more thing: Reminder: create the release tag before 3 PM. (score=0.6997)", "[en] Reminder: contact the applicant by the end of the month. (score=0.8711)", "[en] Also, Make review the approval result the next action and do it by the end of the month. (score=0.861)", "[en] A quick note: Make check the vendor delivery date the next action and do it by the end of the month. (score=0.7974)", "[en] Reminder: contact the applicant after you receive this message. (score=0.8494)", "[en] Make summarize the meeting decisions the next action and do it after you receive this message. (score=0.8998)", "[en] A quick note: Reminder: verify the refund status before the next meeting. (score=0.7043)" ], "testFalsePositiveExamples" : [ "[en] Todo visible only to me: summarize the test results. (score=0.9116)" ], "threshold" : 0.89, "validationBinary" : { "accuracy" : 0.9272, "f1" : 0.84, "falseNegative" : 187, "falsePositive" : 16, "precision" : 0.9709, "recall" : 0.7403, "total" : 2790, "trueNegative" : 2054, "truePositive" : 533 } } ], "id" : "task", "labels" : [ "notTask", "task" ], "positiveLabel" : "task", "selectedAlgorithm" : "maxEnt", "selectedModelFile" : "TaskIntentClassifier.mlmodel" }, { "candidates" : [ { "acceptedForAutomaticRouting" : false, "algorithm" : "maxEnt", "balancedTrainingCount" : 2880, "balancedValidationCount" : 720, "binaryByLanguage" : { "en" : { "accuracy" : 0.9835, "f1" : 0.9318, "falseNegative" : 23, "falsePositive" : 0, "precision" : 1, "recall" : 0.8722, "total" : 1395, "trueNegative" : 1215, "truePositive" : 157 }, "zh-Hans" : { "accuracy" : 0.9885, "f1" : 0.9538, "falseNegative" : 15, "falsePositive" : 1, "precision" : 0.994, "recall" : 0.9167, "total" : 1395, "trueNegative" : 1214, "truePositive" : 165 } }, "confidenceThresholdsByLanguage" : { "en" : 0.89, "zh-Hans" : 0.75 }, "goldenBinary" : { "accuracy" : 0.9575, "f1" : 0.4706, "falseNegative" : 8, "falsePositive" : 1, "precision" : 0.8, "recall" : 0.3333, "total" : 212, "trueNegative" : 199, "truePositive" : 4 }, "goldenBinaryByLanguage" : { "en" : { "accuracy" : 0.9528, "f1" : 0.2857, "falseNegative" : 5, "falsePositive" : 0, "precision" : 1, "recall" : 0.1667, "total" : 106, "trueNegative" : 100, "truePositive" : 1 }, "zh-Hans" : { "accuracy" : 0.9623, "f1" : 0.6, "falseNegative" : 3, "falsePositive" : 1, "precision" : 0.75, "recall" : 0.5, "total" : 106, "trueNegative" : 99, "truePositive" : 3 } }, "goldenFalseNegativeExamples" : [ "[en] The app has crashed constantly since the update, and I lost important data. (score=0.6932)", "[en] The package arrived damaged and the cup inside was broken. (score=0.8516)", "[en] My account was locked for no reason. Can you restore it today? (score=0.4141)", "[en] Messages keep failing to send. Please provide a solution as soon as possible. (score=0.8782)", "[en] Support has not replied for three days. When will this be handled? (score=0.7423)", "[zh-Hans] 收到的商品外包装破损，里面的杯子也碎了。 (score=0.6318)", "[zh-Hans] 消息一直发送失败，请尽快给我一个解决方案。 (score=0.2063)", "[zh-Hans] 客服已经三天没有回复了，请问什么时候能处理？ (score=0.7074)" ], "goldenFalsePositiveExamples" : [ "[zh-Hans] 事情终于解决了，我现在轻松多了。 (score=0.8132)" ], "modelBytes" : 24298, "runtimeAssetIndependent" : true, "testBinary" : { "accuracy" : 0.986, "f1" : 0.9429, "falseNegative" : 38, "falsePositive" : 1, "precision" : 0.9969, "recall" : 0.8944, "total" : 2790, "trueNegative" : 2429, "truePositive" : 322 }, "testFalseNegativeExamples" : [ "[en] Just to add, I need a clear answer: the page loads extremely slowly. How are you going to resolve it? (score=0.639)", "[en] I need a clear answer: messages never send. How are you going to resolve it? (score=0.5932)", "[en] I need a clear answer: the invoice information is wrong. How are you going to resolve it? (score=0.4813)", "[en] I need a clear answer: the order was charged twice. How are you going to resolve it? (score=0.6328)", "[en] I need a clear answer: my reservation disappeared. How are you going to resolve it? (score=0.6104)", "[en] Just to add, I need a clear answer: the app keeps crashing. How are you going to resolve it? (score=0.5869)", "[en] Also, I need a clear answer: the app keeps crashing. How are you going to resolve it? (score=0.4881)", "[en] One more thing: I need a clear answer: the order was charged twice. How are you going to resolve it? (score=0.4748)", "[en] A quick note: I need a clear answer: messages never send. How are you going to resolve it? (score=0.4082)", "[en] A quick note: I need a clear answer: the item arrived damaged. How are you going to resolve it? (score=0.3109)", "[en] One more thing: I need a clear answer: the app keeps crashing. How are you going to resolve it? (score=0.4723)", "[en] Also, I need a clear answer: the page loads extremely slowly. How are you going to resolve it? (score=0.543)" ], "testFalsePositiveExamples" : [ "[zh-Hans] 对于订单状态，这次有没有明确答案？ (score=0.7592)" ], "threshold" : 0.7, "validationBinary" : { "accuracy" : 0.9957, "f1" : 0.9836, "falseNegative" : 1, "falsePositive" : 11, "precision" : 0.9703, "recall" : 0.9972, "total" : 2790, "trueNegative" : 2419, "truePositive" : 359 } } ], "id" : "complaint", "labels" : [ "notComplaint", "complaint" ], "positiveLabel" : "complaint", "selectedAlgorithm" : "maxEnt", "selectedModelFile" : "ComplaintIntentClassifier.mlmodel" } ], "corpusCount" : 16572, "corpusPath" : "ModelTraining/ClipboardSemantics/clipboard_semantic_corpus.jsonl", "generatedAt" : "2026-08-27T01:08:34Z", "goldenCount" : 212, "selectionPolicy" : "Validation only: global and per-language binary thresholds require precision >= 0.97, then maximize recall; languages with fewer than 20 examples per class fall back to the global threshold. sentiment prioritizes macro-F1. Automatic routing also requires a self-contained maxEnt model because BERT embedding assets are not guaranteed in extensions. Test and golden data gate deployment but never tune model weights.", "testCount" : 2790, "trainingCount" : 10780, "validationCount" : 2790 }