{"id":"W2969241968","doi":"10.17605/osf.io/5b63x","title":"CEEA 2018 Systematic Review Workshop Materials","year":2018,"lang":"en","type":"article","venue":"OSF Preprints (OSF Preprints)","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Engineering ethics; Engineering","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":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.02170471,0.0005465627,0.00135201,0.000152592,0.0005002917,0.0006291571,0.003439055,0.0002367378,0.8124626],"category_scores_gemma":[0.0164683,0.0004915007,0.0001824849,0.0004499664,0.0007350133,0.0006367305,0.00248314,0.0002899118,0.9483765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002409128,"about_ca_system_score_gemma":0.0001703038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001770887,"about_ca_topic_score_gemma":0.00002273055,"domain_scores_codex":[0.9908402,0.002715828,0.001661891,0.002806877,0.001025955,0.0009492541],"domain_scores_gemma":[0.9911389,0.0006958268,0.001028589,0.006418569,0.0003726499,0.0003454871],"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":[0.00007771728,0.0001804169,0.0002701548,0.05914108,0.00004869074,0.00002766181,0.0008253917,0.00007916879,0.8826582,0.001448863,0.05512589,0.0001167805],"study_design_scores_gemma":[0.0007923689,0.000009922876,0.00131339,0.07430903,0.0006325061,0.0004206854,0.0001659117,0.0006338919,0.8990074,0.003084688,0.01765041,0.001979777],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.4508383,0.0001191544,0.00979693,0.002311962,0.008338406,0.008682922,0.000110635,0.001717648,0.518084],"genre_scores_gemma":[0.4459488,0.001228537,0.01935665,0.004610653,0.0012731,0.001964256,0.0000453152,0.0002614964,0.5253112],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.135914,"threshold_uncertainty_score":0.9997537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01726874016462792,"score_gpt":0.2874054113441717,"score_spread":0.2701366711795438,"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."}}