{"id":"W7017644500","doi":"","title":"Bulletin de liaison du Partenariat de recherche Familles en mouvance (vol. 13 automne 2016)","year":2016,"lang":"fr","type":"other","venue":"EspaceINRS (National Institute for Scientific Research (Canada))","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Conciliation; Nationality; National library; Information scientist","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":[0.01174413,0.0006771639,0.0007613163,0.002723463,0.0064969,0.008986725,0.001541928,0.004431768,0.07834627],"category_scores_gemma":[0.01594247,0.0005785084,0.0005421108,0.002914676,0.003402976,0.004987648,0.008177349,0.004812636,0.02295622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007309346,"about_ca_system_score_gemma":0.02286808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06591746,"about_ca_topic_score_gemma":0.06903967,"domain_scores_codex":[0.9947171,0.001780671,0.0003667902,0.0006680662,0.00185799,0.0006094315],"domain_scores_gemma":[0.9896781,0.002367761,0.000453062,0.001178918,0.003577288,0.00274486],"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":[0.00003370864,0.0000349439,0.0007227641,0.0002110798,0.000004173009,0.0001217991,0.003561983,0.00003694147,0.0004378945,0.02633337,0.894101,0.07440042],"study_design_scores_gemma":[0.000001436614,0.000004196672,0.000620562,0.0001206613,8.978822e-7,0.00003531017,0.0006407809,0.000008247397,0.00004736726,0.0005020777,0.9980149,0.000003525352],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.005753406,0.1491423,0.004869685,0.2479713,0.07593103,0.0003970172,0.0021842,0.001079207,0.5126719],"genre_scores_gemma":[0.01991934,0.02877356,0.002503074,0.01680406,0.005024744,0.0002812441,0.0008217506,0.0005143367,0.9253579],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.07834627,"threshold_uncertainty_score":0.2620944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1007826732327028,"score_gpt":0.372042004546682,"score_spread":0.2712593313139791,"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."}}