{"id":"W6987249753","doi":"","title":"Spéciation de l'arsenic dans les produits de la pêche par couplage HPLC-ICP-MS après extraction assistée par micro-ondes (MAE). Contribution à l'évaluation des risques par l'estimation de sa bioaccessibilité","year":2008,"lang":"en","type":"dissertation","venue":"INRIA a CCSD electronic archive server","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arsenic; Certified reference materials; Inorganic arsenic; Extraction (chemistry); Solvent extraction; Genetic algorithm; Ion chromatography; Work (physics)","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"],"consensus_categories":[],"category_scores_codex":[0.002339612,0.0006875129,0.0005210078,0.000265199,0.001177598,0.0001887963,0.0004357811,0.0007641811,0.0004116588],"category_scores_gemma":[0.001025575,0.0007501221,0.0003087097,0.0004966839,0.0004517729,0.001037233,0.00007355015,0.001023405,0.0000920381],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005104802,"about_ca_system_score_gemma":0.001090767,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00185416,"about_ca_topic_score_gemma":0.02425314,"domain_scores_codex":[0.9944406,0.00150363,0.001003433,0.001063257,0.0008133056,0.001175788],"domain_scores_gemma":[0.9975225,0.000520307,0.001078107,0.0005006668,0.0001507621,0.0002276151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006427739,0.0006651864,0.1314251,0.0002468193,0.0002567035,0.00001971169,0.01660245,0.006290338,0.7372523,0.0016169,0.001329252,0.1036525],"study_design_scores_gemma":[0.001159799,0.0001963703,0.7990405,0.000211424,0.0003414313,0.00007762098,0.0004773348,0.03849933,0.1451705,0.01246406,0.001664701,0.0006969098],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9587309,0.0003232466,0.03628395,0.0001128588,0.0001756465,0.001461923,0.00007844042,0.0002598853,0.002573157],"genre_scores_gemma":[0.9874128,0.001459563,0.004189441,0.00008296414,0.0002062853,0.0004823669,0.00477304,0.0001055225,0.001288002],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6676154,"threshold_uncertainty_score":0.999495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0117685754885212,"score_gpt":0.2732729952570896,"score_spread":0.2615044197685685,"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."}}