{"id":"W2780997921","doi":"","title":"D’Aurore à Avatar / FALARDEAU, Éric. Une histoire des effets spéciaux au Québec, Montréal, Éditions Somme toute, 2017, 275 p.","year":2018,"lang":"fr","type":"article","venue":"Érudit (Université de Montréal)","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Avatar; Art; Literature","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":[0.0014413,0.001077874,0.0006913511,0.003581875,0.007479377,0.005841725,0.001807082,0.002440846,0.03728544],"category_scores_gemma":[0.003872406,0.0004963017,0.0004754555,0.006421692,0.004037326,0.005998592,0.001354302,0.002925545,0.009462359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02110817,"about_ca_system_score_gemma":0.01704865,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9166469,"about_ca_topic_score_gemma":0.9632811,"domain_scores_codex":[0.9990765,0.0001648525,0.00003450174,0.00007874897,0.0005039788,0.0001412697],"domain_scores_gemma":[0.9968992,0.0006278573,0.0001135264,0.00007672929,0.002079153,0.0002036074],"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":[0.00003979972,0.00001501605,0.001021704,0.0005320651,0.00001640782,0.0001718404,0.01102091,0.00008221965,0.0002420791,0.01443312,0.8962004,0.0762245],"study_design_scores_gemma":[0.000006306464,0.000005277245,0.004197137,0.0007967433,0.00001284248,0.0001154073,0.007545054,0.00003488068,0.00017889,0.001331465,0.9857599,0.00001604386],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002632138,0.812398,0.001676255,0.09950718,0.008783014,0.00003801424,0.001882279,0.000214922,0.07286815],"genre_scores_gemma":[0.1050504,0.4904296,0.003873362,0.01840798,0.004066458,0.0001494151,0.001191894,0.0006603382,0.3761707],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.0833531,"threshold_uncertainty_score":0.1676879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05297824872846581,"score_gpt":0.2158203490837592,"score_spread":0.1628421003552935,"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."}}