{"id":"W4387185473","doi":"10.3233/faia230559","title":"Investigating the Learning Behaviour of In-Context Learning: A Comparison with Supervised Learning","year":2023,"lang":"en","type":"book-chapter","venue":"Frontiers in artificial intelligence and applications","topic":"Topic Modeling","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Dalhousie University; Vector Institute; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Context (archaeology); Computer science; Task (project management); Artificial intelligence; Machine learning; Cognitive psychology; Psychology; Geography; 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":[0.0005773458,0.0002436457,0.000427618,0.00032858,0.0002754199,0.0001169453,0.0006558601,0.0001805567,0.000005482746],"category_scores_gemma":[0.00007625014,0.0002142785,0.00005867238,0.0003521019,0.0002766136,0.0001327642,0.0002224819,0.001430054,0.00001608741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000543987,"about_ca_system_score_gemma":0.0001012182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001872304,"about_ca_topic_score_gemma":0.0003914194,"domain_scores_codex":[0.9980444,0.0000785641,0.0007357023,0.000580543,0.0002817082,0.0002790589],"domain_scores_gemma":[0.998899,0.000217063,0.0003649725,0.0003626986,0.00008999594,0.00006627844],"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":[0.000006540302,0.00003110509,0.03755078,0.00005032755,0.00002376208,0.000003782292,0.008795875,0.1133562,0.00003698115,0.3416758,0.00002627782,0.4984426],"study_design_scores_gemma":[0.00006728524,0.0001409612,0.0003830277,0.0005322236,0.00003354129,0.000003800331,0.01207941,0.8863988,0.0003726924,0.09408465,0.005405874,0.0004977459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004262073,0.0005244844,0.9885555,0.0003967774,0.0001122556,0.0006716051,0.000001415681,0.0001231582,0.005352766],"genre_scores_gemma":[0.9699011,0.0003041709,0.01657782,0.00004120217,0.0001065029,0.0002318132,0.00002079738,0.00005642095,0.01276014],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9719777,"threshold_uncertainty_score":0.8738022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07672128964706759,"score_gpt":0.2897408337165567,"score_spread":0.2130195440694891,"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."}}