{"id":"W4292230097","doi":"10.1080/09553002.2022.2110312","title":"Development of an adverse outcome pathway for radiation-induced microcephaly via expert consultation and machine learning","year":2022,"lang":"en","type":"review","venue":"International Journal of Radiation Biology","topic":"Effects of Radiation Exposure","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Norsk Institutt for Vannforskning; Norges Miljø- og Biovitenskapelige Universitet; Bundesamt für Strahlenschutz; Norges Forskningsråd; Réseau de cancérologie Rossy","keywords":"Microcephaly; Adverse Outcome Pathway; Context (archaeology); Alliance; Neuroscience; Biology; Medicine; Psychology; Bioinformatics; Computational biology; Pediatrics; Political science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01553065,0.0009366678,0.0005978568,0.005635222,0.001514824,0.002916666,0.00281123,0.002059819,0.01198999],"category_scores_gemma":[0.03265665,0.0002840206,0.001146206,0.002039551,0.001310651,0.002276461,0.003379431,0.001720461,0.002452858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002179103,"about_ca_system_score_gemma":0.007950203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003809188,"about_ca_topic_score_gemma":0.006410242,"domain_scores_codex":[0.9879705,0.007314119,0.0006864155,0.001178259,0.00216978,0.0006809581],"domain_scores_gemma":[0.9739962,0.01562219,0.001992332,0.001086052,0.006104582,0.001198739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0004986491,0.0009039639,0.03175348,0.003359388,0.0002820142,0.004888904,0.008450238,0.0171605,0.00830296,0.0451922,0.05825057,0.8209572],"study_design_scores_gemma":[0.0003064401,0.001289194,0.03548658,0.006432846,0.0009607058,0.007740788,0.02037041,0.3252921,0.03428262,0.1963147,0.3709354,0.0005882374],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.1067629,0.005038702,0.7406104,0.0340332,0.0006389506,0.003813109,0.002837792,0.003808412,0.1024565],"genre_scores_gemma":[0.4789059,0.002353618,0.501965,0.002632333,0.0002992537,0.00120111,0.001979579,0.0001784481,0.01048473],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01553065,"threshold_uncertainty_score":0.0821349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06080775484248214,"score_gpt":0.3882450574647768,"score_spread":0.3274373026222947,"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."}}