{"id":"W2734975679","doi":"10.1186/s12935-017-0440-8","title":"The prognostic value of miR-126 expression in non-small-cell lung cancer: a meta-analysis","year":2017,"lang":"en","type":"article","venue":"Cancer Cell International","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Program for New Century Excellent Talents in University; Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Meta-analysis; Lung cancer; Medicine; microRNA; Value (mathematics); Oncology; Expression (computer science); Internal medicine; Pathology; Bioinformatics; Cancer research; Computer science; Biology; Machine learning; Genetics; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001588779,0.0001215428,0.0001956754,0.00004061327,0.0001089468,0.00005481795,0.0005823362,0.00007646006,0.0002435008],"category_scores_gemma":[0.00003811794,0.00009082431,0.0003429787,0.00004433334,0.00006953528,0.000009387404,0.0001725608,0.00005641324,0.000001151622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006815448,"about_ca_system_score_gemma":0.0001201534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006559759,"about_ca_topic_score_gemma":0.001214999,"domain_scores_codex":[0.9991,0.00004245062,0.000251856,0.000283386,0.0001834987,0.000138854],"domain_scores_gemma":[0.9989323,0.00002352753,0.0003646415,0.0004700253,0.0001674625,0.00004202846],"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":[0.00008728873,0.0001095969,0.07376423,0.00005127339,0.007031176,0.000001961332,0.00008106464,0.008043266,0.9087766,0.00002688962,0.001761171,0.0002654208],"study_design_scores_gemma":[0.0006786998,0.00002029003,0.08915804,0.00002205055,0.008539167,3.752808e-7,0.00003342912,0.01044652,0.8862839,0.00003497202,0.004580897,0.0002016279],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9788001,0.01643053,0.001229721,0.0003478512,0.0003301076,0.0003346477,0.000143897,0.000003420754,0.002379687],"genre_scores_gemma":[0.9965593,0.0009784866,0.0002565193,0.00004236774,0.0001376212,0.0002650889,0.00007517108,0.00001303411,0.001672453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02249274,"threshold_uncertainty_score":0.3703708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01997492004500794,"score_gpt":0.3069710130473091,"score_spread":0.2869960930023011,"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."}}