{"id":"W4394534038","doi":"10.6084/m9.figshare.20882150","title":"Additional file 3 of Strategies for understanding the role of cellular heterogeneity in the pathogenesis of lung cancer: a cell model for chronic exposure to cigarette smoke extract","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Genomics, phytochemicals, and oxidative stress","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Food Inspection Agency","funders":"","keywords":"Cigarette smoke; Pathogenesis; Lung cancer; Smoke; Cancer research; Medicine; Biology; Bioinformatics; Oncology; Chemistry; Pathology; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001754637,0.001596365,0.00209477,0.002363608,0.0009554633,0.002582968,0.002761417,0.002388078,0.5538167],"category_scores_gemma":[0.01646642,0.000792643,0.001962072,0.004076723,0.0004207898,0.001757355,0.00158198,0.001590903,0.1039972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001293133,"about_ca_system_score_gemma":0.002175994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01063534,"about_ca_topic_score_gemma":0.02061198,"domain_scores_codex":[0.9991062,0.0001602397,0.0001374682,0.000310901,0.000156753,0.000128434],"domain_scores_gemma":[0.9901921,0.007355857,0.0005321806,0.0007092253,0.0008741621,0.0003365508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004079561,0.00007019527,0.003130556,0.009660483,0.0001980559,0.00007190912,0.00005992318,0.0007970709,0.0003223656,0.0009576926,0.9801743,0.004149535],"study_design_scores_gemma":[0.006864046,0.0002120705,0.02006559,0.004459902,0.0005746316,0.0003213364,0.0002343302,0.001735334,0.001123838,0.008139263,0.9561466,0.0001230153],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000444833,0.0000226113,0.00003973264,0.00003006379,0.000005581753,0.00001211724,0.999645,0.00006795143,0.0001324731],"genre_scores_gemma":[0.001551494,0.00009407103,0.0007462177,0.0001722989,0.00001765955,0.0004604934,0.9955859,0.000180005,0.001191947],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5538167,"threshold_uncertainty_score":0.6364263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0372293974657039,"score_gpt":0.2721581443489671,"score_spread":0.2349287468832632,"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."}}