{"id":"W2017275588","doi":"10.1504/ijmme.2009.029320","title":"GenRel: A computerised model for reliability prediction of mining machinery","year":2009,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reliability (semiconductor); Reliability engineering; Computer science; Engineering; Data mining","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001633205,0.0005943301,0.0008159159,0.0007339606,0.0003423773,0.0009859477,0.002120567,0.001395904,0.003079144],"category_scores_gemma":[0.006827911,0.0005395856,0.0008498981,0.0006870064,0.0006132629,0.001078964,0.0006795388,0.001321015,0.0005693829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001366409,"about_ca_system_score_gemma":0.0009473283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01379498,"about_ca_topic_score_gemma":0.008590565,"domain_scores_codex":[0.9995496,0.0001907589,0.0000221503,0.0001061107,0.00009285105,0.00003858405],"domain_scores_gemma":[0.9973967,0.00191072,0.000237092,0.0001344922,0.0002530439,0.00006797334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002298642,0.00001709968,0.000648543,0.00001530738,0.00001431783,0.00002419358,0.00001311911,0.9906088,0.0001363471,0.003230455,0.0005041071,0.004764731],"study_design_scores_gemma":[0.000002869466,0.000005511899,0.00007003626,0.000001248931,0.000001795481,0.000005481333,8.274708e-7,0.9979787,0.00002443766,0.001740712,0.0001665571,0.000001902507],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05696054,0.0003631362,0.9357721,0.0006622944,0.00009598029,0.0001049579,0.001231349,0.001194449,0.003615199],"genre_scores_gemma":[0.7807668,0.0005446548,0.2092427,0.0002743187,0.000132437,0.0005003503,0.001701168,0.0001970823,0.006640587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01379498,"threshold_uncertainty_score":0.0274294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0130361454749475,"score_gpt":0.2339735718412456,"score_spread":0.2209374263662981,"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."}}