{"id":"W7098275805","doi":"","title":"DESIGN CRITERIA AND SAFETY EVALUATIONS AT CLOSURE","year":2015,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tailings; Closure (psychology); Tailings dam; Safety case; Commission; Dam failure","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003341956,0.0001220912,0.0001540333,0.00004231687,0.0002798842,0.0001833991,0.0002446364,0.00005093352,0.005872515],"category_scores_gemma":[0.0006708281,0.00009560542,0.00001372526,0.0001090017,0.0001820214,0.0002670739,0.0002458595,0.00004571555,0.00124609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007304328,"about_ca_system_score_gemma":0.0001096821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008506024,"about_ca_topic_score_gemma":0.00001649276,"domain_scores_codex":[0.9982768,0.0004805478,0.0002344498,0.0003510561,0.0004005361,0.000256569],"domain_scores_gemma":[0.999159,0.0001483322,0.00007479975,0.0002973182,0.0001306297,0.0001899668],"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":[0.0001003064,0.00001894395,0.002482702,0.00001029926,0.000001630013,0.000003583818,0.0008685985,0.003243743,0.9783247,0.001260886,0.01348779,0.0001968353],"study_design_scores_gemma":[0.004015268,0.00104919,0.05026836,0.00008201627,0.00009294979,0.0004147313,0.0005434548,0.2024502,0.6782485,0.02177976,0.03941732,0.001638161],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9016714,0.00008501331,0.08483314,0.00134531,0.0009357515,0.0003194382,0.000009871634,0.0002455268,0.01055463],"genre_scores_gemma":[0.8343936,0.00000591714,0.1607002,0.000389297,0.0001107258,0.00002257687,0.000005127877,0.00001606275,0.004356565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3000761,"threshold_uncertainty_score":0.9995316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06798641405986916,"score_gpt":0.3536395465295342,"score_spread":0.2856531324696651,"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."}}