{"id":"W2732826855","doi":"10.4050/f-0073-2017-12086","title":"Wear Sensors for Pitch Control Bearing Condition Based Maintenance","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell Helicopter Textron (Canada)","funders":"","keywords":"Bearing (navigation); Control (management); Automotive engineering; Computer science; Environmental science; Engineering; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004939502,0.0004185985,0.0004989014,0.0006224441,0.0002164334,0.0005045093,0.0008647837,0.000540962,0.003751626],"category_scores_gemma":[0.001481138,0.0002869706,0.0001910635,0.0003780224,0.0001519214,0.0008789368,0.0002963996,0.000489237,0.0007501299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003527554,"about_ca_system_score_gemma":0.0002527283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006855958,"about_ca_topic_score_gemma":0.001380797,"domain_scores_codex":[0.999188,0.00007986217,0.00003294023,0.00008470604,0.0005746695,0.00003967106],"domain_scores_gemma":[0.9988979,0.0002945144,0.0001668166,0.0001475318,0.0004536981,0.00003956012],"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":[0.0007050683,0.0001964422,0.006662415,0.0006320731,0.00004407375,0.0002303028,0.0001703836,0.004013914,0.6583858,0.001286751,0.007496769,0.3201759],"study_design_scores_gemma":[0.0001521048,0.001944764,0.03851911,0.0001286685,0.0001053754,0.00198537,0.000199759,0.1251096,0.7751017,0.001524504,0.05509681,0.0001322555],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3525023,0.008868985,0.6020483,0.0008077147,0.001273794,0.0006938582,0.002528484,0.01311432,0.01816225],"genre_scores_gemma":[0.8520526,0.0009449709,0.1334481,0.0002661985,0.0001156715,0.0001429609,0.0007681868,0.0001326379,0.01212867],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003751626,"threshold_uncertainty_score":0.01255047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008476746970321485,"score_gpt":0.2487172797822887,"score_spread":0.2402405328119673,"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."}}