{"id":"W7084085371","doi":"10.64628/aap.76npnsxku","title":"Laïcité, vous dites? Séparez d’abord l’argent de l’État!","year":2019,"lang":"fr","type":"article","venue":"","topic":"Scientific Research and Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Set (abstract data type); Identification (biology); Relation (database); Feature (linguistics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002211755,0.00105461,0.000883027,0.0009453227,0.006718921,0.007910618,0.0007445971,0.004406271,0.06134921],"category_scores_gemma":[0.00841999,0.0003684312,0.0005825954,0.0009056346,0.005282351,0.009091732,0.003182798,0.01129355,0.01867409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005117595,"about_ca_system_score_gemma":0.003879874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03661761,"about_ca_topic_score_gemma":0.05057719,"domain_scores_codex":[0.9981362,0.0006124765,0.00005511042,0.0003612803,0.0004432705,0.0003917339],"domain_scores_gemma":[0.9980591,0.0004846303,0.0001679067,0.000205929,0.000761719,0.0003207353],"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":[0.0001893628,0.00003411817,0.001257547,0.0002013958,0.00002616045,0.000513336,0.00544932,0.0001153519,0.0006703421,0.2993382,0.6541372,0.03806762],"study_design_scores_gemma":[0.000008644207,0.000007523473,0.0004316619,0.00009936455,0.000003423397,0.00008994999,0.001105923,0.00002585633,0.00008083336,0.00558867,0.9925433,0.00001480659],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.008322837,0.03928112,0.003175463,0.6233571,0.0585562,0.0000362409,0.0007084295,0.0005727666,0.2659898],"genre_scores_gemma":[0.08849847,0.01456004,0.002797346,0.09078354,0.01481137,0.0000974142,0.0004025129,0.001563547,0.7864859],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.06134921,"threshold_uncertainty_score":0.2052336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03205184457078251,"score_gpt":0.291058311951254,"score_spread":0.2590064673804715,"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."}}