{"id":"W7144928317","doi":"","title":"カナダにおける「クリティカル・シンキング」","year":2002,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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":[0.004223417,0.0004136109,0.0003178247,0.002719469,0.005030559,0.01234926,0.001094931,0.001529557,0.0214598],"category_scores_gemma":[0.01026779,0.0005482294,0.0004864559,0.003147611,0.006624247,0.008339539,0.001843343,0.001806804,0.005838826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01244413,"about_ca_system_score_gemma":0.01808471,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1203683,"about_ca_topic_score_gemma":0.1428979,"domain_scores_codex":[0.9965001,0.0006623036,0.0003227105,0.000636469,0.001457873,0.0004204522],"domain_scores_gemma":[0.9906413,0.001954854,0.0006704317,0.001133799,0.004458984,0.0011406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002016587,0.0001438986,0.02093873,0.0004731392,0.00009602327,0.0003578651,0.01386693,0.001465233,0.002578673,0.6085942,0.1089665,0.2423172],"study_design_scores_gemma":[0.00005069657,0.00006518352,0.02809102,0.0004489977,0.0001096789,0.0003544243,0.01430294,0.001374304,0.004511485,0.1333365,0.8172464,0.0001082688],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05520111,0.005967325,0.02804185,0.03598332,0.001220803,0.0003557086,0.002529569,0.0005882636,0.870112],"genre_scores_gemma":[0.6722541,0.006024629,0.04253352,0.004774652,0.0005564729,0.0002925258,0.002124118,0.0002357259,0.2712042],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8796317,"threshold_uncertainty_score":0.2393354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01944589890812741,"score_gpt":0.2211828698669175,"score_spread":0.2017369709587901,"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."}}