{"id":"W2491818457","doi":"10.4018/978-1-60566-310-4.ch022","title":"Ethology-Based Approximate Adaptive Learning","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Ethology; Artificial intelligence; Computer science; Animal learning; Machine learning; Adaptive learning; Adaptive behavior; Psychology; Biology; Ecology; Cognitive psychology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003221542,0.0005682357,0.0005702087,0.0001217555,0.0002425998,0.000193384,0.001134536,0.0005204143,0.0000201724],"category_scores_gemma":[0.00003341407,0.0005523611,0.0002950817,0.00003788262,0.0001143168,0.00006394917,0.0002769199,0.001281368,0.000321316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001513074,"about_ca_system_score_gemma":0.0002473581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003091498,"about_ca_topic_score_gemma":0.000005084114,"domain_scores_codex":[0.9975672,0.000103778,0.0003629848,0.0009399467,0.0004894811,0.0005365919],"domain_scores_gemma":[0.9985075,0.00007216028,0.0003624441,0.000742598,0.0001184917,0.0001968115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000116616,0.000007435384,0.000004805043,0.00001091031,0.00002734153,0.0001880181,0.00004781292,0.0006850136,0.000002981083,0.843477,0.0003501379,0.1551869],"study_design_scores_gemma":[0.000907258,0.0009691367,0.00006101026,0.000388746,0.00006779279,0.0001816856,0.000006021869,0.1175046,0.00004211577,0.7587218,0.1196799,0.00146992],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000005761726,0.0001967085,0.200992,0.0002120797,0.0003387562,0.000179599,0.000009602379,0.0007571095,0.7973084],"genre_scores_gemma":[0.05744353,0.000006140046,0.2795311,0.004520472,0.00111028,0.00003401399,0.00002040827,0.0001424653,0.6571916],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1537169,"threshold_uncertainty_score":0.9996928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01744949488195298,"score_gpt":0.2525665531601567,"score_spread":0.2351170582782037,"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."}}