{"id":"W2400456651","doi":"","title":"A Comparison of Case Acquisition Strategies for Learning from Observations of State-Based Experts.","year":2013,"lang":"en","type":"article","venue":"The Florida AI Research Society","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Chunking (psychology); Artificial intelligence; Machine learning; Similarity (geometry); Context (archaeology); Knowledge acquisition; State (computer science); Focus (optics); Data mining; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001551922,0.0001051934,0.000210831,0.00004629345,0.0006009412,0.0002127071,0.0006247743,0.00006846066,0.00003032031],"category_scores_gemma":[0.000113009,0.00007911951,0.0001435106,0.0004768288,0.0002088955,0.0005057442,0.0001446306,0.0003743192,0.000004536922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004868565,"about_ca_system_score_gemma":0.0003609989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003273726,"about_ca_topic_score_gemma":0.00002492423,"domain_scores_codex":[0.9982155,0.0003404274,0.0003261878,0.0002385941,0.000515159,0.0003641533],"domain_scores_gemma":[0.995966,0.002562406,0.0001461095,0.0004474358,0.0008113898,0.00006662238],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001438508,0.0004908669,0.03118152,0.0007152504,0.0004051631,0.00001781245,0.2164503,0.3708088,0.1858518,0.0151914,0.1664451,0.01229812],"study_design_scores_gemma":[0.00039483,0.0002805796,0.001377914,0.00008868766,0.000006874072,0.000001523347,0.01085894,0.9634352,0.01399729,0.009055231,0.0003946764,0.00010819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5509445,0.0002274504,0.4467105,0.001566851,0.00006216112,0.0003878079,0.00001916748,0.00005072623,0.00003083096],"genre_scores_gemma":[0.9646564,0.000005854773,0.03492346,0.00009942727,0.00006141084,0.0001464338,0.00003527051,0.000009778752,0.00006201243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5926265,"threshold_uncertainty_score":0.4948916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1816502049657346,"score_gpt":0.4049998242487162,"score_spread":0.2233496192829815,"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."}}