{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000595912,0.00008965247,0.0001002697,0.0001327713,0.0002630252,0.0005379709,0.0003547367,0.00003702894,0.00005470802],"category_scores_gemma":[0.0001370375,0.00008102864,0.00002330153,0.0002192669,0.00001045858,0.0004533118,0.0001324944,0.0002162095,0.00009234343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001679996,"about_ca_system_score_gemma":0.00001827581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001063675,"about_ca_topic_score_gemma":0.000001405675,"domain_scores_codex":[0.9990467,0.00006901029,0.0001285503,0.0002914702,0.0002483279,0.0002159107],"domain_scores_gemma":[0.9995165,0.0000914724,0.00003952969,0.0001814588,0.00003825071,0.0001327697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003321157,0.00001387649,0.0005791933,0.000002537867,0.000004754053,0.000009743269,0.03164635,0.001626635,0.001021454,0.3636998,0.0006374357,0.6007549],"study_design_scores_gemma":[0.001688559,0.001458417,0.05711942,0.0001567934,0.0000140911,0.00009962268,0.005907535,0.2513321,0.001231063,0.2600549,0.4194234,0.00151409],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02146783,0.00007750094,0.9270242,0.006440419,0.00009967124,0.00007709093,2.790888e-8,0.0003763745,0.04443691],"genre_scores_gemma":[0.6645801,0.000005792859,0.3257892,0.005545164,0.00003555934,0.00000120676,2.562846e-7,0.000004281341,0.004038405],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6431122,"threshold_uncertainty_score":0.5187666,"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."}}