{"id":"W2141794039","doi":"10.1109/pacrim.1997.620322","title":"Neural network stereo image segmentation for directed coordinate measuring machine part programming","year":2002,"lang":"en","type":"article","venue":"","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Artificial intelligence; Computer vision; Computer science; Digitization; Robustness (evolution); Stereo camera; Segmentation; Computer stereo 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000312658,0.0001440881,0.0001439675,0.00004671529,0.0001377192,0.0003175722,0.0003894157,0.00003596911,0.00008822922],"category_scores_gemma":[0.00004427424,0.0001187549,0.0000673747,0.0002313096,0.00002565724,0.0007047338,0.00009687251,0.00008807422,0.00001645401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003682259,"about_ca_system_score_gemma":0.000003429411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009946922,"about_ca_topic_score_gemma":0.00001314247,"domain_scores_codex":[0.9988174,0.00004748407,0.0002457498,0.0002988502,0.0002088898,0.000381559],"domain_scores_gemma":[0.999426,0.00005243099,0.00006693346,0.0002349222,0.0001421758,0.0000775522],"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":[0.00003333152,0.0002715528,0.003961974,0.00007833265,0.00006103639,0.000006148761,0.0003297782,0.00003516511,0.01274181,0.01354997,0.01952796,0.9494029],"study_design_scores_gemma":[0.0007860669,0.000779447,0.0006450651,0.0001066367,0.00002481641,0.000006658405,0.00001899227,0.9403834,0.04765738,0.00174634,0.007313807,0.0005313875],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005604899,0.0001797028,0.9763592,0.001158653,0.0004562443,0.0009917455,0.000001442998,0.002118364,0.01312976],"genre_scores_gemma":[0.6773089,0.000009192283,0.3215892,0.0001788947,0.0001083892,0.0001561853,0.00000389789,0.00001136898,0.0006339907],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9488716,"threshold_uncertainty_score":0.4842684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07044881784740652,"score_gpt":0.2693018596956396,"score_spread":0.1988530418482331,"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."}}