{"id":"W2122010129","doi":"10.1109/robot.1994.351336","title":"Crack detection using contact sensing","year":2002,"lang":"en","type":"article","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Visibility; Computer science; Robot; Computer vision; Artificial intelligence; Optics; Physics","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":[0.0002332877,0.0005126997,0.0006390611,0.0009772023,0.0004150421,0.0008174567,0.0009681024,0.001364836,0.003103098],"category_scores_gemma":[0.001608059,0.0003729433,0.0004280946,0.0005001976,0.0006613756,0.001803036,0.00134117,0.000593945,0.0007918291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003519097,"about_ca_system_score_gemma":0.0002693363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001103685,"about_ca_topic_score_gemma":0.001243029,"domain_scores_codex":[0.9992695,0.00005402161,0.00002518591,0.000191194,0.0004160415,0.00004404307],"domain_scores_gemma":[0.998807,0.0004785904,0.0001496258,0.0002148936,0.0002801418,0.00006975043],"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":[0.0003590147,0.0001626919,0.002514219,0.0004890318,0.00006657388,0.0005832103,0.0002890996,0.03088927,0.6680368,0.008902709,0.0024402,0.2852673],"study_design_scores_gemma":[0.0000409198,0.0004626038,0.00350803,0.0000435408,0.00004788191,0.001421444,0.00007343408,0.7562582,0.2240496,0.005244345,0.008754006,0.00009605472],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06736188,0.001011989,0.9222699,0.0001663926,0.0001297472,0.0001262541,0.0001016545,0.001828348,0.007003901],"genre_scores_gemma":[0.7100852,0.0007089865,0.2830521,0.0001683592,0.00007876764,0.00009684188,0.000166859,0.000133619,0.005509234],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003103098,"threshold_uncertainty_score":0.01038092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04530185074884446,"score_gpt":0.2193892545733357,"score_spread":0.1740874038244913,"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."}}