{"id":"W6917909717","doi":"10.58079/p7r5","title":"LE MARCHÉ GLOBAL DES VÉHICULES D’OCCASION : FLUX NORD-SUD (II)","year":2022,"lang":"fr","type":"article","venue":"Industrias Culturais (Universidade de Coimbra)","topic":"China's Global Influence and Migration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Flux (metallurgy); Field (mathematics); Work (physics); Noise (video)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006983534,0.000420704,0.0004072525,0.0001386147,0.007265894,0.000269822,0.001064138,0.0005853709,0.003055563],"category_scores_gemma":[0.0002631729,0.0004606626,0.0003704473,0.003140554,0.001259962,0.001669865,0.0007836944,0.001009927,0.0002220348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003115873,"about_ca_system_score_gemma":0.001587515,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05543504,"about_ca_topic_score_gemma":0.0206561,"domain_scores_codex":[0.995724,0.001033392,0.00038537,0.0007186944,0.0009931186,0.001145412],"domain_scores_gemma":[0.9984105,0.0001120125,0.0003317793,0.0003566376,0.0002664223,0.0005226816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002585807,0.0008386335,0.00527296,0.00005372865,0.0002472875,0.0004786748,0.02665062,0.002979642,0.002899818,0.5183735,0.3569431,0.08500336],"study_design_scores_gemma":[0.00137487,0.0004136891,0.05369462,0.0001217123,0.0001587083,0.0001457853,0.07999605,0.0001957551,0.0002153102,0.004703311,0.8583181,0.000662109],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7987914,0.002472941,0.00008611566,0.0755296,0.001641687,0.0006342002,0.0008131156,0.0002260759,0.1198049],"genre_scores_gemma":[0.9049885,0.0003364324,0.0002687971,0.000893222,0.0006163296,0.00002486269,0.0002688332,0.00002422014,0.09257879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5136703,"threshold_uncertainty_score":0.9997845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04157374896635099,"score_gpt":0.2813065811330421,"score_spread":0.2397328321666911,"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."}}