{"id":"W6910246702","doi":"10.4224/40002762","title":"La science à l'oeuvre pour le Canada : rapport annuel du CNRC 2001-2002","year":2002,"lang":"fr","type":"report","venue":"NRC Digital Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Government (linguistics); Context (archaeology); Work (physics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","research_integrity"],"category_scores_codex":[0.002973586,0.002431851,0.002260846,0.001156905,0.001943156,0.004353606,0.003850283,0.001445298,0.0002834966],"category_scores_gemma":[0.005605856,0.00278871,0.0009710677,0.002980719,0.005558577,0.005222153,0.001436507,0.002612411,0.002987527],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.0202778,"about_ca_system_score_gemma":0.2434753,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6577456,"about_ca_topic_score_gemma":0.1583081,"domain_scores_codex":[0.976658,0.00033438,0.003075671,0.003888063,0.01206673,0.003977167],"domain_scores_gemma":[0.9825814,0.0005297327,0.002924528,0.003477153,0.007417682,0.003069506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004802534,0.00139014,0.01762828,0.0004882265,0.0004243596,0.02212426,0.0002484806,0.0001807659,0.002815622,0.0001443807,0.9156376,0.03886987],"study_design_scores_gemma":[0.0007656679,0.0001586309,0.01739417,0.001044106,0.0003040682,0.02927499,0.0006458843,0.0003987901,0.001304397,0.00002615806,0.9459807,0.002702493],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.03311545,0.01027152,0.000023999,0.000192073,0.01144516,0.001079504,0.00178793,0.0005297946,0.9415546],"genre_scores_gemma":[0.4077102,0.0002396284,0.0001094655,0.00008407146,0.002440808,0.00008387759,0.0001137013,0.0006017546,0.5886165],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4994375,"threshold_uncertainty_score":0.999851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03086209412676829,"score_gpt":0.2246914120523312,"score_spread":0.1938293179255629,"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."}}