{"id":"W2417345431","doi":"10.1016/j.joen.2016.04.020","title":"A Micro–Computed Tomographic Assessment of the Influence of Operator's Experience on the Quality of WaveOne Instrumentation","year":2016,"lang":"en","type":"article","venue":"Journal of Endodontics","topic":"Endodontics and Root Canal Treatments","field":"Dentistry","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Huazhong University of Science and Technology; Canada Foundation for Innovation","keywords":"Computed tomographic; Instrumentation (computer programming); Operator (biology); Quality assessment; Quality (philosophy); Materials science; Medical physics; Biomedical engineering; Nuclear medicine; Computer science; Medicine; Computed tomography; Reliability engineering; Engineering; Radiology; Physics; Evaluation methods; Chemistry; Operating system","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":[0.000847903,0.0002899457,0.0002280079,0.0009711625,0.0001944533,0.0004437144,0.0002609566,0.0004857062,0.002937513],"category_scores_gemma":[0.004892114,0.0003153711,0.0003646975,0.000629048,0.0004898795,0.0003897333,0.0002767264,0.0003554973,0.0002167287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002057334,"about_ca_system_score_gemma":0.0002765547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002734902,"about_ca_topic_score_gemma":0.002678474,"domain_scores_codex":[0.9993868,0.0001795624,0.00006636532,0.0001023968,0.0001957182,0.00006913616],"domain_scores_gemma":[0.9920384,0.004659833,0.001031323,0.0004511645,0.001455309,0.0003640021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.01924847,0.001205027,0.4059434,0.0002518535,0.0003216343,0.003030317,0.002228696,0.002143094,0.4587798,0.0001324337,0.0005333159,0.106182],"study_design_scores_gemma":[0.00006649668,0.005499117,0.950049,0.00001596537,0.0002190544,0.002663976,0.0006224307,0.004734013,0.03511635,0.00006908398,0.0008541435,0.00009030173],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956324,0.0002605219,0.003030475,0.0000330949,0.00001056647,0.00002603615,0.0001001319,0.00003098961,0.0008757733],"genre_scores_gemma":[0.9976072,0.0001006132,0.001692978,0.00002829352,0.00001519373,0.00001197571,0.00007691359,0.00001950402,0.0004471295],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002937513,"threshold_uncertainty_score":0.009827018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03578086005274107,"score_gpt":0.3507675328969274,"score_spread":0.3149866728441863,"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."}}