{"id":"W6995953595","doi":"","title":"PrÃ©fÃ©rence pour les titres nationaux et modÃ¨le international d'Ã©valuation des actifs financiers avec capital humain","year":2000,"lang":"fr","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Capital (architecture); Human capital; Investment (military)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.003027051,0.0008603323,0.0006196467,0.002505576,0.002692178,0.008231873,0.001384852,0.002628543,0.09961971],"category_scores_gemma":[0.008511726,0.0004568628,0.0007472197,0.002570782,0.001069417,0.00202436,0.001078784,0.002791054,0.01344926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02068509,"about_ca_system_score_gemma":0.03216945,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6217211,"about_ca_topic_score_gemma":0.5929126,"domain_scores_codex":[0.9968126,0.0002477362,0.0001200277,0.000348448,0.001945999,0.0005251793],"domain_scores_gemma":[0.9959485,0.0006980881,0.0002473492,0.0002808364,0.002301097,0.0005242024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005162123,0.0001469982,0.004707185,0.0002609394,0.00003974184,0.0001580629,0.0007464922,0.001262149,0.001025462,0.2514812,0.62561,0.1140456],"study_design_scores_gemma":[0.00005891922,0.00003382868,0.0167465,0.0001057002,0.0000143943,0.00006308036,0.0001908464,0.0009160055,0.001245722,0.004149806,0.9764453,0.00002978955],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01635724,0.01028757,0.004746641,0.01741531,0.002145594,0.0003022582,0.02130898,0.001351125,0.9260854],"genre_scores_gemma":[0.04026911,0.001761041,0.002429557,0.0004511954,0.0002038158,0.0001488378,0.002580199,0.0002717644,0.9518845],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6217211,"threshold_uncertainty_score":0.7610133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006627508052065935,"score_gpt":0.1703542622818439,"score_spread":0.163726754229778,"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."}}