{"id":"W7067048084","doi":"","title":"Le langage graphique des Ã©motions, identification d'Ã©motions exprimÃ©es par le dessin","year":2001,"lang":"fr","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Identification (biology); Context (archaeology); Feature (linguistics); Perspective (graphical)","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":[0.0005962992,0.001638025,0.0006294202,0.001896099,0.001113187,0.003858218,0.0005728091,0.001530601,0.0190755],"category_scores_gemma":[0.001926769,0.0006167829,0.001231557,0.001134775,0.001458378,0.003187865,0.0008684997,0.001934904,0.009489889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001524927,"about_ca_system_score_gemma":0.001216588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.052247,"about_ca_topic_score_gemma":0.02939031,"domain_scores_codex":[0.9988526,0.0001815504,0.00006670971,0.000357348,0.0004489321,0.00009290159],"domain_scores_gemma":[0.9987761,0.0004800124,0.0001308367,0.0001793726,0.0003458546,0.00008768875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0006683619,0.00017965,0.006769747,0.0007531423,0.0001271454,0.001662254,0.002689219,0.01940885,0.06805172,0.5283535,0.07259778,0.2987388],"study_design_scores_gemma":[0.0001346694,0.0002874046,0.01929437,0.0003024525,0.00009155071,0.00196851,0.001418382,0.1001136,0.05864479,0.1892049,0.6282578,0.0002816783],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08333987,0.001317439,0.8183569,0.001579056,0.0009689664,0.0002693046,0.01198225,0.01391287,0.06827319],"genre_scores_gemma":[0.3749472,0.002869311,0.3367935,0.0005265895,0.0005932819,0.0004108286,0.02470594,0.003862609,0.2552909],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.052247,"threshold_uncertainty_score":0.1038858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0041754919804668,"score_gpt":0.1509217314825667,"score_spread":0.1467462395020999,"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."}}