{"id":"W3121688979","doi":"","title":"Les circuits courts alimentaires : vers une logistique plus verte ?","year":2014,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"French Urban and Social Studies","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Transports","funders":"","keywords":"Humanities; Political science; Forestry; Physics; Geography; Art","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":[0.0007527945,0.000263551,0.0002731177,0.001273187,0.002388984,0.008104337,0.0008548867,0.001407934,0.01585618],"category_scores_gemma":[0.002823244,0.0002296972,0.0003237765,0.001596391,0.004209981,0.006368164,0.001424632,0.0009521773,0.001029425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007180981,"about_ca_system_score_gemma":0.003239455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05339303,"about_ca_topic_score_gemma":0.06738353,"domain_scores_codex":[0.998762,0.000356038,0.00003954384,0.000264219,0.0003262451,0.0002520277],"domain_scores_gemma":[0.9982949,0.0003876372,0.0003986178,0.000197275,0.0005430759,0.0001785545],"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":[0.0002322641,0.0000460537,0.05346498,0.0003513993,0.00005371868,0.001028387,0.02038776,0.002165074,0.01127039,0.7688649,0.008608373,0.1335269],"study_design_scores_gemma":[0.00003979202,0.0002648442,0.2792258,0.000609297,0.0001176944,0.001792013,0.06000779,0.00642456,0.006194013,0.1461589,0.49902,0.0001452492],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.613026,0.008329585,0.04536285,0.02349928,0.0002615997,0.0001082897,0.0007916554,0.0002961845,0.3083246],"genre_scores_gemma":[0.9606337,0.001479638,0.004219021,0.0005281272,0.00004823188,0.00002986158,0.0001274204,0.00004984956,0.03288405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05339303,"threshold_uncertainty_score":0.1061645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03886872943276952,"score_gpt":0.2643671611300357,"score_spread":0.2254984316972661,"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."}}