{"id":"W2119183988","doi":"10.1109/crv.2008.44","title":"Development of Continuum Shape Constraint Analysis (CSCA) for Computer Vision Applications Using Range Data","year":2008,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Constraint (computer-aided design); Computer science; Artificial intelligence; Feature (linguistics); Mathematical optimization; Pattern recognition (psychology); Data mining; Computer vision; Mathematics","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":[0.001827316,0.001046804,0.001269149,0.002858382,0.0007625362,0.002148904,0.002209199,0.001196116,0.002307994],"category_scores_gemma":[0.006911182,0.0008841622,0.001791754,0.003037574,0.001741178,0.002090812,0.002157965,0.002497681,0.001501444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001167306,"about_ca_system_score_gemma":0.001971034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0057031,"about_ca_topic_score_gemma":0.003638467,"domain_scores_codex":[0.9976801,0.0003832797,0.0001156638,0.0002944694,0.001448552,0.00007780298],"domain_scores_gemma":[0.9954218,0.001736454,0.0003360147,0.0006658506,0.001700245,0.000139565],"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":[0.00005423005,0.00008786363,0.001340284,0.0003188876,0.0001252645,0.000249152,0.0002114195,0.2881707,0.02494225,0.1806346,0.003945117,0.4999201],"study_design_scores_gemma":[0.000003897891,0.00003199923,0.0002790446,0.00002136456,0.000007119404,0.00007709825,0.0000213657,0.9641347,0.003558491,0.02516522,0.006667521,0.00003218322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006997439,0.00007868365,0.9983869,0.00003679927,0.00001215612,0.00002858708,0.00002539614,0.0001458079,0.0005859386],"genre_scores_gemma":[0.04780877,0.0003856806,0.9496729,0.00007621118,0.0000780472,0.0002593636,0.0002090676,0.0002782653,0.001231694],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0057031,"threshold_uncertainty_score":0.01133978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06856727832740687,"score_gpt":0.2815591517468852,"score_spread":0.2129918734194783,"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."}}