{"id":"W7015662719","doi":"","title":"27th CCLA Annual Meeting/ Le congrès annuel de l’ACLC: Université du Quebec à Montréal, 1995","year":2020,"lang":"fr","type":"other","venue":"York University Digital Library (York University)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Economic shortage; Outbreak; Selection (genetic algorithm)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001171571,0.001286262,0.000777835,0.001681412,0.004636016,0.005183166,0.001602578,0.002153126,0.4276618],"category_scores_gemma":[0.00227725,0.0005396697,0.0007449751,0.001843519,0.001148805,0.001489744,0.001865664,0.00176565,0.1374591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02184016,"about_ca_system_score_gemma":0.03271795,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8706378,"about_ca_topic_score_gemma":0.952782,"domain_scores_codex":[0.9991441,0.00006701451,0.00003075703,0.00009747969,0.0003534104,0.0003073195],"domain_scores_gemma":[0.9974774,0.00009490312,0.00004716532,0.00009543634,0.001536169,0.000748921],"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":[0.00005501608,0.00003912058,0.0009487527,0.00004684662,0.000006119179,0.00006108652,0.00006307179,0.00007758503,0.0001284008,0.001060081,0.9768827,0.02063113],"study_design_scores_gemma":[0.00001562722,0.000009060279,0.00383431,0.00008107098,0.000006753735,0.00002467033,0.0002180949,0.0001169979,0.0001498715,0.0002066453,0.9953244,0.00001240071],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01031254,0.01800917,0.002576137,0.05049673,0.01824373,0.0005310691,0.0269514,0.001598536,0.8712807],"genre_scores_gemma":[0.005830728,0.001520149,0.0005640883,0.0005358859,0.0003096576,0.00005255016,0.002361624,0.0002171136,0.9886082],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4276618,"threshold_uncertainty_score":0.816371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006753058068232517,"score_gpt":0.1413422607274327,"score_spread":0.1345892026592002,"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."}}