{"id":"W2033263268","doi":"10.1109/coginf.2007.4341930","title":"Autolearner: An Autonomic Machine Learning System Based on Concept Algebra","year":2007,"lang":"en","type":"article","venue":"","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Process calculus; Process (computing); Representation (politics); Knowledge representation and reasoning; Cognition; Artificial intelligence; Cognitive model; Object (grammar); Relation (database); Informatics; Human–computer interaction; Theoretical computer science; Programming language; Data mining; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005349847,0.0003754309,0.0005199247,0.0003756577,0.0002675438,0.000879403,0.001574525,0.0005624313,0.006413556],"category_scores_gemma":[0.001522903,0.000251013,0.0002861139,0.0002563777,0.0003869233,0.002603705,0.001374157,0.0007846719,0.001262977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002656578,"about_ca_system_score_gemma":0.0004939479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005506932,"about_ca_topic_score_gemma":0.0005437798,"domain_scores_codex":[0.9998037,0.00003824119,0.00001535439,0.00007558956,0.00005413943,0.000012976],"domain_scores_gemma":[0.9994493,0.0002241568,0.00005093444,0.0001313993,0.00006592744,0.000078281],"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":[0.00100709,0.001204049,0.007133036,0.0004761098,0.0002270071,0.001058723,0.001257681,0.05962153,0.09705873,0.0473004,0.01453703,0.7691186],"study_design_scores_gemma":[0.0002296542,0.0006635292,0.002625052,0.00006631827,0.0001067365,0.001221337,0.0001137158,0.845832,0.04380396,0.04921054,0.05601188,0.0001152887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06563099,0.0002410425,0.8756632,0.0002038635,0.00007106588,0.000260335,0.0002333374,0.0489673,0.008728912],"genre_scores_gemma":[0.5008121,0.000349531,0.4851791,0.0003378136,0.00005982142,0.0004099135,0.0008482686,0.0008527812,0.01115083],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006413556,"threshold_uncertainty_score":0.02145547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01168062090331676,"score_gpt":0.2362052671430558,"score_spread":0.2245246462397391,"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."}}