{"id":"W4381433614","doi":"10.1016/j.fuel.2023.128992","title":"Automatic fracture detection from the images of electrical image logs using Mask R-CNN","year":2023,"lang":"en","type":"article","venue":"Fuel","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"China Scholarship Council","keywords":"Computer science; Convolutional neural network; Artificial intelligence; Pattern recognition (psychology); Inpainting; Image (mathematics); Segmentation; Deep learning; Precision and recall; Computer vision","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":[0.0002045278,0.0009549045,0.0005892992,0.001093105,0.0001886999,0.0004872439,0.0009982645,0.0007190713,0.002068359],"category_scores_gemma":[0.0006211385,0.0003702262,0.0007500799,0.0006418017,0.0002338378,0.000534074,0.0005769551,0.0005808956,0.001345137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003824827,"about_ca_system_score_gemma":0.0005779592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008039863,"about_ca_topic_score_gemma":0.01405691,"domain_scores_codex":[0.999828,0.000008394903,0.000006218153,0.00005300113,0.00005936622,0.00004504944],"domain_scores_gemma":[0.999828,0.00002685406,0.0000246592,0.00003302942,0.00007486514,0.00001253548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005364299,0.0002013217,0.008221672,0.000334872,0.0001455715,0.0004009524,0.00006584017,0.04464364,0.1471562,0.001196917,0.01428937,0.7828072],"study_design_scores_gemma":[0.00001180323,0.000115563,0.01177408,0.00003826325,0.00008536665,0.0003475078,0.00004966033,0.9183503,0.063834,0.001306696,0.004062109,0.00002471437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2861868,0.001675333,0.6892087,0.0004704279,0.0003199366,0.0002217819,0.003203721,0.01071053,0.008002718],"genre_scores_gemma":[0.7247574,0.001046599,0.2558855,0.0002813903,0.0001112265,0.0001278678,0.005289172,0.0004229502,0.012078],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008039863,"threshold_uncertainty_score":0.01598614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006563614159796284,"score_gpt":0.2193679413035055,"score_spread":0.2128043271437092,"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."}}