{"id":"W2774073476","doi":"10.1016/j.foodchem.2017.12.043","title":"Thermal degradation of chloramphenicol in model solutions, spiked tissues and incurred samples","year":2017,"lang":"en","type":"article","venue":"Food Chemistry","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"McGill University","keywords":"Degradation (telecommunications); Chloramphenicol; Chemistry; Veterinary Drugs; Residue (chemistry); Chromatography; Kinetics; Liquid chromatography–mass spectrometry; Environmental chemistry; Mass spectrometry; Biochemistry; Veterinary medicine; Antibiotics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002519993,0.0003671716,0.0001994121,0.0001577451,0.000233516,0.0002384066,0.0002108553,0.0003501282,0.001351815],"category_scores_gemma":[0.0004246684,0.0001396656,0.0002331545,0.000199162,0.0002771187,0.0001458026,0.000114366,0.0002792825,0.0003074287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005408752,"about_ca_system_score_gemma":0.0005568619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004347234,"about_ca_topic_score_gemma":0.006471935,"domain_scores_codex":[0.9997723,0.00003892713,0.00001469038,0.00006204068,0.00006115063,0.0000510069],"domain_scores_gemma":[0.9998474,0.00004350092,0.00003252471,0.00001784454,0.0000439657,0.00001465205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003632348,0.00001503841,0.0003787328,0.0000539306,0.000009085501,0.00003599027,0.00002825089,0.000320816,0.9975109,0.00003116299,0.00002952702,0.001223334],"study_design_scores_gemma":[0.000004553862,0.0003141175,0.00190056,0.000007511745,0.00001268898,0.00006969563,0.00003603998,0.0006167954,0.9966858,0.00001516459,0.0003332017,0.000003834748],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922592,0.0006833404,0.004725663,0.00003555591,0.00001745031,0.0000420896,0.0006002558,0.00003652859,0.001599823],"genre_scores_gemma":[0.9927344,0.000591016,0.003516859,0.00003279377,0.000005808135,0.00004355907,0.0006639346,0.00001412715,0.002397428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004347234,"threshold_uncertainty_score":0.008643866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05890454425690376,"score_gpt":0.2900543817221996,"score_spread":0.2311498374652958,"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."}}