{"id":"W3027864372","doi":"10.1016/j.cell.2020.04.034","title":"Identification of ALK in Thinness","year":2020,"lang":"en","type":"article","venue":"Cell","topic":"Adipose Tissue and Metabolism","field":"Medicine","cited_by":110,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Hospital for Sick Children; University of Toronto","funders":"Horizon 2020; Österreichischen Akademie der Wissenschaften; Hjärnfonden; Natural Science Foundation of Guangdong Province; Instituto Mexicano del Petróleo; Boehringer Ingelheim; Austrian Science Fund; Vetenskapsrådet; Seventh Framework Programme; Eesti Teadusagentuur; European Research Council; Österreichische Forschungsförderungsgesellschaft; Novo Nordisk Fonden; National Natural Science Foundation of China; European Regional Development Fund; European Commission","keywords":"Biology; Gene knockdown; Genetics; Population; Single-nucleotide polymorphism; Endocrinology; Internal medicine; Gene; Cancer research; Genotype","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":[],"consensus_categories":[],"category_scores_codex":[0.0002849534,0.0004707721,0.0002000642,0.001084552,0.0004593217,0.0009580307,0.0003302129,0.0006124515,0.004432829],"category_scores_gemma":[0.0002877196,0.0002509235,0.000406039,0.0004182226,0.000540373,0.0005835354,0.0006191352,0.001200069,0.001359903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003604335,"about_ca_system_score_gemma":0.0003252938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006381448,"about_ca_topic_score_gemma":0.000698623,"domain_scores_codex":[0.9998794,0.00001576502,0.00001248046,0.00002628207,0.00003413506,0.00003202762],"domain_scores_gemma":[0.9997719,0.00003541929,0.00005859317,0.00002482683,0.00005820704,0.00005109077],"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":[0.001030824,0.0000800074,0.01743953,0.0002208157,0.0000635332,0.003338723,0.0001402089,0.0001474887,0.960797,0.002582999,0.0005195926,0.01363926],"study_design_scores_gemma":[0.0001386092,0.0007412895,0.1407772,0.0002271837,0.000323626,0.02261121,0.001811397,0.001955699,0.7744105,0.003576387,0.05338009,0.00004692626],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9715148,0.01194511,0.004429606,0.001082215,0.0002998812,0.00005333136,0.0009452047,0.0001108789,0.009619005],"genre_scores_gemma":[0.9818583,0.0051467,0.00291895,0.0003167917,0.00009876469,0.0000317525,0.001417879,0.00002600817,0.008185011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004432829,"threshold_uncertainty_score":0.01482928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02152741635487414,"score_gpt":0.2691334241667946,"score_spread":0.2476060078119204,"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."}}