{"id":"W7019097366","doi":"","title":"Evaluation of innovative water treatments at molecular level based on high resolution mass spectrometry and advanced statistical analysis tools","year":2019,"lang":"en","type":"other","venue":"Universitat de Girona Digital Repository (Universitat de Girona)","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission; Ministerio de Ciencia e Innovación; Canadian Institute for Advanced Research","keywords":"High resolution; Statistical analysis; Mass spectrometry; Analytical Chemistry (journal); High mass","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002341065,0.000650836,0.0005743341,0.001253573,0.0003091779,0.001339773,0.0006622687,0.0006058358,0.001965893],"category_scores_gemma":[0.002926897,0.0002101364,0.001001045,0.0007694418,0.0004380986,0.001093612,0.0007030616,0.0004688303,0.0004607385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007820003,"about_ca_system_score_gemma":0.0009740127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002069237,"about_ca_topic_score_gemma":0.004112448,"domain_scores_codex":[0.9985782,0.0003735588,0.00007751284,0.0001916819,0.0006979117,0.00008114558],"domain_scores_gemma":[0.9984445,0.0005720573,0.0001980494,0.0001215435,0.0006138848,0.00004994133],"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":[0.003519712,0.001710849,0.02445613,0.0009129995,0.0007119438,0.000130904,0.0001949981,0.06118658,0.4923303,0.004425966,0.002508113,0.4079114],"study_design_scores_gemma":[0.0001789422,0.003500348,0.03326081,0.00005350379,0.0005642684,0.00009753428,0.00028655,0.3510404,0.5986492,0.0044797,0.007759613,0.0001292441],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7474227,0.001695806,0.2400024,0.0004493076,0.0002053403,0.0005379688,0.001335997,0.00169304,0.006657389],"genre_scores_gemma":[0.8661033,0.0008851464,0.1274425,0.0001699675,0.00004424271,0.0002289258,0.001163177,0.0002218448,0.003740834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002341065,"threshold_uncertainty_score":0.01238084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01858919877974943,"score_gpt":0.2472801940181811,"score_spread":0.2286909952384317,"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."}}