{"id":"W4402616149","doi":"10.3390/cancers16183179","title":"Metabolomic Profiling of Pulmonary Neuroendocrine Neoplasms","year":2024,"lang":"en","type":"article","venue":"Cancers","topic":"Lung Cancer Research Studies","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières; Centre hospitalier universitaire de Québec; University of Alberta; Université Laval; The Metabolomics Innovation Centre; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval; Institut de Valorisation des Données; MEDTEQ+; Mitacs","keywords":"Metabolomics; Profiling (computer programming); Computational biology; Medicine; Pathology; Bioinformatics; Biology; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.00007420705,0.0001026168,0.0002516807,0.0001273404,0.00002744078,0.00000921073,0.00007205014,0.00001273571,0.0001079846],"category_scores_gemma":[0.00008283672,0.00008034759,0.00009268307,0.0003326083,0.0001327498,0.00006508677,0.00005991977,0.0002019637,0.00002730876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005718287,"about_ca_system_score_gemma":0.00086823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001703276,"about_ca_topic_score_gemma":0.000006357355,"domain_scores_codex":[0.9990652,0.00001718841,0.0001654642,0.0002417163,0.0002571232,0.0002533463],"domain_scores_gemma":[0.9995717,0.00006757346,0.00002117467,0.0001955615,0.00005816261,0.00008587254],"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":[0.002351375,0.00007950843,0.02896104,0.0128773,0.002566884,0.006328202,0.001106336,0.001472517,0.7249461,0.005218375,0.06220266,0.1518897],"study_design_scores_gemma":[0.001897166,0.0008180719,0.01091532,0.001730477,0.0008318548,0.0008869124,0.0009990698,0.03201789,0.6953241,0.0004928616,0.2535826,0.0005037567],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9107071,0.05859734,0.00009133156,0.00311629,0.001488406,0.0008362226,0.00006205567,0.0002756075,0.02482561],"genre_scores_gemma":[0.9946066,0.002225086,0.0002807004,0.0001376962,0.0002375474,0.0000720301,0.000008434813,0.00002744497,0.00240443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1913799,"threshold_uncertainty_score":0.3276479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02517799578675142,"score_gpt":0.3437458890967281,"score_spread":0.3185678933099767,"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."}}