{"id":"W3006488808","doi":"10.3390/s20041057","title":"Detection System for U-Shaped Bellows Convolution Pitches Based on a Laser Line Scanner","year":2020,"lang":"en","type":"article","venue":"Sensors","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China; Government of Jiangsu Province","keywords":"Bellows; Convolution (computer science); Expansion joint; Laser scanning; Scanner; Sample (material); Computer science; Line (geometry); Laser; Engineering; Mechanical engineering; Artificial intelligence; Structural engineering; Mathematics; Optics","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":[0.0006572457,0.0005242535,0.000616754,0.001606203,0.0003640756,0.0005739497,0.001291451,0.001105053,0.002664239],"category_scores_gemma":[0.0008091276,0.0004654115,0.0004118098,0.0009334993,0.0003213556,0.001261343,0.0007825934,0.0007113653,0.001152175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004984646,"about_ca_system_score_gemma":0.0007543262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009951683,"about_ca_topic_score_gemma":0.001397634,"domain_scores_codex":[0.9992613,0.00008866946,0.00003615965,0.0001932789,0.0003622397,0.00005831068],"domain_scores_gemma":[0.99905,0.0001751812,0.00009339988,0.0001152906,0.0004984867,0.00006760424],"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":[0.0004371927,0.0001553923,0.006748828,0.000208092,0.00005302867,0.000290427,0.0003180085,0.00322024,0.6075149,0.001559455,0.005815241,0.3736792],"study_design_scores_gemma":[0.0001561058,0.0006982808,0.01698709,0.00006460745,0.0001271004,0.002160009,0.0002431352,0.4643454,0.499166,0.00104896,0.01477977,0.0002236112],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1041689,0.0004257089,0.8856851,0.000241223,0.0001260107,0.0001629341,0.0002488845,0.006404879,0.002536355],"genre_scores_gemma":[0.3940217,0.0002976196,0.6007466,0.0002565908,0.00008966987,0.0002347581,0.0003906264,0.000161706,0.003800646],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002664239,"threshold_uncertainty_score":0.008912742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02641181345906965,"score_gpt":0.2154899225173082,"score_spread":0.1890781090582385,"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."}}