{"id":"W2940135435","doi":"","title":"Vers une utilisation éco-efficace des matières premières minérales","year":2012,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Outotec (Canada)","funders":"","keywords":"Medicine; Political science","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":[0.0008638066,0.0005100931,0.0006804182,0.0004696923,0.00039497,0.001398548,0.0003987763,0.0007361086,0.004576746],"category_scores_gemma":[0.0008770152,0.000249157,0.0006236884,0.0006221807,0.0004093799,0.0009090703,0.0004045098,0.0006107748,0.001168288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006742641,"about_ca_system_score_gemma":0.0004855123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002384272,"about_ca_topic_score_gemma":0.004098656,"domain_scores_codex":[0.9993156,0.0001110659,0.00003184527,0.0001895183,0.0002702344,0.00008182914],"domain_scores_gemma":[0.9995013,0.0002021865,0.00009148543,0.00004573345,0.0001399066,0.0000193611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004789936,0.0001142075,0.002244012,0.0007240663,0.00005983884,0.0001703035,0.0001250962,0.005226337,0.9473992,0.00166681,0.0001678379,0.04162325],"study_design_scores_gemma":[0.00001843695,0.0007965384,0.004197292,0.00005936191,0.00006329657,0.0001634954,0.00008560784,0.00448567,0.9757034,0.0005231314,0.01388654,0.00001713863],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.934989,0.01430943,0.02594538,0.000397932,0.00009573942,0.00007009477,0.0003278567,0.0002412167,0.02362337],"genre_scores_gemma":[0.9679064,0.004647456,0.009836835,0.0001098934,0.00002432405,0.00003751106,0.0001351238,0.00008049471,0.01722185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004576746,"threshold_uncertainty_score":0.0153107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02256838152109689,"score_gpt":0.2323220393413608,"score_spread":0.2097536578202639,"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."}}