{"id":"W3083168257","doi":"10.1139/tcsme-2020-0049","title":"A low-cost three-dimensional reconstruction and monitoring system using digital fringe projection","year":2020,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Projection (relational algebra); Process (computing); Obstacle; System of measurement; Structured-light 3D scanner; Computer vision; Artificial intelligence; Algorithm","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006327251,0.0006559673,0.0007814025,0.0009434296,0.0004336362,0.0008277897,0.001827398,0.0009158219,0.003115653],"category_scores_gemma":[0.0008949835,0.0005269104,0.0004402509,0.0006176588,0.0004513175,0.001714663,0.001035028,0.0006997822,0.001269358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004486112,"about_ca_system_score_gemma":0.0009785752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001371209,"about_ca_topic_score_gemma":0.001625875,"domain_scores_codex":[0.9991799,0.0000838833,0.00003508267,0.0001823483,0.000464681,0.00005409073],"domain_scores_gemma":[0.999365,0.000133116,0.00008329414,0.0001421378,0.0002186468,0.00005783968],"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":[0.00029138,0.0001506821,0.003227052,0.0004307317,0.00006436616,0.0003552192,0.0002022988,0.004908052,0.5013746,0.004796445,0.004711022,0.4794882],"study_design_scores_gemma":[0.0001725184,0.001602269,0.0117071,0.00009078761,0.0002075305,0.004802665,0.0001653445,0.215699,0.6792971,0.001866915,0.08390833,0.0004804188],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01688334,0.0002449517,0.9787426,0.0001271435,0.00007882678,0.0001298821,0.0001311792,0.002178742,0.001483377],"genre_scores_gemma":[0.1501392,0.0003084702,0.8455521,0.0001744763,0.0000604325,0.0001978916,0.0002955274,0.00008001937,0.003191993],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003115653,"threshold_uncertainty_score":0.01042289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03693293685973181,"score_gpt":0.2167271456562812,"score_spread":0.1797942087965494,"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."}}