{"id":"W2119808881","doi":"10.1145/1553374.1553480","title":"Learning when to stop thinking and do something!","year":2009,"lang":"en","type":"article","venue":"","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Task (project management); Face (sociological concept); Artificial intelligence; Entropy (arrow of time); Quality (philosophy); Sequence (biology); Gradient descent; Machine learning; Artificial neural network; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002441531,0.000977113,0.0008228739,0.000311398,0.0005766722,0.001163824,0.001339656,0.001328203,0.006022913],"category_scores_gemma":[0.01071605,0.0004164937,0.000406613,0.0001952788,0.001199579,0.00285116,0.0007538002,0.00251813,0.003840641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004625859,"about_ca_system_score_gemma":0.0009820688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001464781,"about_ca_topic_score_gemma":0.002252431,"domain_scores_codex":[0.9992722,0.0002785142,0.0000321929,0.0002493575,0.00009211178,0.00007568596],"domain_scores_gemma":[0.9969427,0.001546473,0.0002846456,0.0004737374,0.0004763832,0.0002761147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001615937,0.0008330386,0.01072059,0.0003995511,0.0002905412,0.0003019727,0.0007885551,0.08928802,0.03147986,0.03701494,0.03797594,0.789291],"study_design_scores_gemma":[0.0001332746,0.0005500743,0.003518191,0.0001082084,0.00008703688,0.0002650437,0.0003479502,0.8495488,0.02571139,0.1045441,0.01505821,0.000127761],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07626316,0.0006674021,0.9055473,0.003661553,0.0003659776,0.0001738928,0.0001692488,0.004672355,0.008479141],"genre_scores_gemma":[0.5727939,0.0004996728,0.407115,0.001833623,0.0001778375,0.0002743496,0.0003860019,0.0006085794,0.01631105],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006022913,"threshold_uncertainty_score":0.02014863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01445949601614374,"score_gpt":0.2534198717970605,"score_spread":0.2389603757809168,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}