{"id":"W2578735219","doi":"10.20965/jaciii.2000.p0187","title":"Sampling Research on Advanced Computational Intelligence in Canada","year":2000,"lang":"en","type":"article","venue":"Journal of Advanced Computational Intelligence and Intelligent Informatics","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Computational intelligence; Diversity (politics); Selection (genetic algorithm); Library science; Intelligence analysis; Operations research; Artificial intelligence; Data science; Sociology; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00554197,0.0007587445,0.001170842,0.00847014,0.01053108,0.01234738,0.00180137,0.001716312,0.04050107],"category_scores_gemma":[0.01885594,0.0006836447,0.0006914153,0.02680412,0.006393014,0.00549783,0.003539218,0.003231223,0.003260496],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.1511123,"about_ca_system_score_gemma":0.2348821,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9789504,"about_ca_topic_score_gemma":0.9830179,"domain_scores_codex":[0.9920852,0.000942597,0.0002847158,0.0006640403,0.0047691,0.001254489],"domain_scores_gemma":[0.982176,0.002658644,0.0004840999,0.0007111239,0.01160326,0.002366807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001423434,0.00008380666,0.009667326,0.0005064642,0.00005546027,0.0001596025,0.002826381,0.00155629,0.0002510514,0.5855405,0.2453651,0.1538456],"study_design_scores_gemma":[0.00005499788,0.00004038024,0.02188354,0.001003871,0.0000504924,0.0001268252,0.006378997,0.003763181,0.0004356086,0.08101629,0.8851642,0.00008166786],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03114624,0.1001446,0.009888276,0.147837,0.00469956,0.0003319391,0.004194965,0.0002641389,0.7014935],"genre_scores_gemma":[0.4720146,0.1706111,0.01260124,0.01443639,0.001375085,0.0002807528,0.004182066,0.0003211171,0.3241777],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8488877,"threshold_uncertainty_score":0.9845894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0725059410162873,"score_gpt":0.3655839460822779,"score_spread":0.2930780050659906,"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."}}