{"id":"W4293063382","doi":"10.1073/pnas.2210407119","title":"Reply to Dablander and Bury: Dealing with the unknown unknowns of deep learning","year":2022,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Ecosystem dynamics and resilience","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Waterloo","funders":"","keywords":"Ecology; Biosphere; Microbial population biology; Community; Glacier; Phylogenetic tree; Biology; Environmental ethics; Ecosystem; Paleontology; Philosophy; Bacteria","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001540537,0.00005723553,0.0000904848,0.00004671511,0.0005188602,0.00001327496,0.0006240433,0.00001474759,0.00004624149],"category_scores_gemma":[0.0001076475,0.00002950665,0.0000227241,0.0006472188,0.0005942355,0.0001359322,0.0004692206,0.0001412737,4.583007e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003253906,"about_ca_system_score_gemma":0.000006605266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000533521,"about_ca_topic_score_gemma":0.000001730229,"domain_scores_codex":[0.9985291,0.000009525957,0.0001700113,0.0001959408,0.0009845382,0.0001109007],"domain_scores_gemma":[0.9995568,0.00009137939,0.0002830704,0.000008825662,0.00003288953,0.00002706327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007036456,0.00007879724,0.355891,0.00009429953,0.00003100532,3.482366e-8,0.004364837,0.2478225,0.3040195,0.08461995,0.0003705468,0.002637126],"study_design_scores_gemma":[0.0005889967,0.0008741125,0.7622454,0.0001888708,0.00005338474,0.0001021167,0.01032638,0.137163,0.05463021,0.02154244,0.01181567,0.0004693481],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870977,0.00005340658,0.000006946858,0.004085892,0.000006824646,0.0001444867,0.000002387388,0.000003812428,0.008598534],"genre_scores_gemma":[0.9989445,0.000009110423,0.0005544826,0.0002627741,0.000008047264,0.000009095118,2.901238e-8,0.000002587169,0.0002093975],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4063545,"threshold_uncertainty_score":0.3990705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01124816801582297,"score_gpt":0.240847839098742,"score_spread":0.229599671082919,"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."}}