{"id":"W2990377400","doi":"10.1016/j.talanta.2019.120585","title":"High-resolution mass spectrometry for molybdenum speciation in sulfidic waters","year":2019,"lang":"en","type":"article","venue":"Talanta","topic":"Radioactive element chemistry and processing","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trent University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Molybdenum; Genetic algorithm; Molybdate; Sulfide; Reactivity (psychology); Electrospray ionization; Mass spectrometry; Chloride; Sulfur; Inorganic chemistry; Thio-; Ionic bonding; Ion; Medicinal chemistry; Chromatography; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000132096,0.000124994,0.0001573041,0.00005539613,0.00004156104,0.00003436737,0.0001305183,0.00009838252,0.001015739],"category_scores_gemma":[0.00002283801,0.0001278386,0.0000483864,0.0001163801,0.00001476364,0.000160929,0.00001588869,0.0001334828,0.0000609241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002134321,"about_ca_system_score_gemma":0.00002295987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000188055,"about_ca_topic_score_gemma":0.000002501981,"domain_scores_codex":[0.9991037,0.000006923274,0.0001950916,0.0002653663,0.0001499679,0.0002789624],"domain_scores_gemma":[0.9996113,0.00005706692,0.00009806977,0.0001763621,0.00001993515,0.00003728937],"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":[0.0001202776,0.00003467748,0.02101474,0.000230824,0.00001799555,0.000003304841,0.00008284365,0.00006695466,0.9776581,0.0001267871,0.0002904311,0.0003530629],"study_design_scores_gemma":[0.001183152,0.00001738508,0.001828116,0.00007022527,0.00001228883,0.000005136466,0.0001600155,0.0003708888,0.9940149,0.0008149029,0.001339822,0.0001831538],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893851,0.00007085664,0.0002857964,0.0001234041,0.0001267806,0.00009248071,0.00003817241,0.00004459496,0.009832807],"genre_scores_gemma":[0.9949664,0.00001979159,0.0002956825,0.00002238291,0.0003153758,0.00001705133,0.0002705744,0.0000180102,0.004074723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01918663,"threshold_uncertainty_score":0.9998975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009023522785452117,"score_gpt":0.2301831571827596,"score_spread":0.2211596343973075,"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."}}