{"id":"W6992227344","doi":"","title":"La modernisation du programme d'intégration au travail pour les nouvelles infirmières du CHUQ","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":"Modernization theory; Government (linguistics); Context (archaeology); Field (mathematics)","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":[0.003246707,0.0005476907,0.0002874051,0.001757771,0.004534345,0.00534413,0.001529378,0.002197847,0.08166358],"category_scores_gemma":[0.004946974,0.000470889,0.0004583489,0.002315734,0.002000096,0.001408915,0.002588809,0.002366357,0.007937855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02538897,"about_ca_system_score_gemma":0.07720243,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8156746,"about_ca_topic_score_gemma":0.801122,"domain_scores_codex":[0.9968559,0.0005323628,0.00008935517,0.0002476515,0.001214806,0.001059867],"domain_scores_gemma":[0.9957771,0.0006039079,0.0001756995,0.0004352524,0.00182066,0.001187241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003844288,0.0004802721,0.01952722,0.0005562388,0.00003138866,0.0004870976,0.01147055,0.001575405,0.004204651,0.1989983,0.2646852,0.4975992],"study_design_scores_gemma":[0.00003379604,0.00005896282,0.03817232,0.0001434059,0.000006567939,0.00009630655,0.00146946,0.0003409541,0.0007042582,0.0009604286,0.9579973,0.00001637633],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.09118301,0.01091004,0.009447705,0.02729226,0.00168362,0.001087143,0.003809141,0.001483615,0.8531035],"genre_scores_gemma":[0.1074562,0.002267525,0.005671379,0.001120759,0.0001318629,0.0002609317,0.001142117,0.0002562001,0.881693],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1843254,"threshold_uncertainty_score":0.3708218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006200497658960909,"score_gpt":0.1492213156476579,"score_spread":0.143020817988697,"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."}}