{"id":"W3084673114","doi":"10.3390/cancers12092653","title":"Classifying Lung Neuroendocrine Neoplasms through MicroRNA Sequence Data Mining","year":2020,"lang":"en","type":"article","venue":"Cancers","topic":"Neuroendocrine Tumor Research Advances","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Weill Cornell Medical College; Génome Québec; McGill University","keywords":"microRNA; Neuroendocrine tumors; Small Cell Lung Carcinoma; Pathology; Biology; Lung; Pathological; Lung cancer; Computational biology; Small-cell carcinoma; Medicine; Internal medicine; Gene; Genetics","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":[0.002278401,0.0008065681,0.001459633,0.005011849,0.0005603955,0.001513893,0.0009896467,0.0008338082,0.0005948552],"category_scores_gemma":[0.005234984,0.0003087758,0.001314346,0.002877871,0.0003376102,0.0008627845,0.0006652729,0.0008498738,0.0008155439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005469559,"about_ca_system_score_gemma":0.001165668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001755338,"about_ca_topic_score_gemma":0.002861892,"domain_scores_codex":[0.998109,0.0003099166,0.0004619532,0.000616098,0.0003763773,0.0001267178],"domain_scores_gemma":[0.9974781,0.001228338,0.0004355525,0.0002245685,0.0005150065,0.0001184751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00171835,0.001269971,0.2060122,0.002225654,0.000904399,0.003397085,0.0005669729,0.03387265,0.1431456,0.001728174,0.008414732,0.5967441],"study_design_scores_gemma":[0.000223332,0.001460961,0.1198914,0.000544022,0.001103353,0.006625246,0.001475294,0.6947729,0.1194864,0.01147959,0.04269555,0.0002420144],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.715664,0.006331651,0.2370524,0.001159965,0.000199688,0.00141802,0.03137583,0.003693437,0.003105021],"genre_scores_gemma":[0.6152964,0.00179147,0.3282588,0.0003566656,0.0001123867,0.001074856,0.05215223,0.0001477233,0.0008094446],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005011849,"threshold_uncertainty_score":0.0120495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1555561398641091,"score_gpt":0.3928839582758323,"score_spread":0.2373278184117232,"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."}}