{"id":"W7044120335","doi":"","title":"Valutazione delle prestazioni di sistemi di acquisizione tipo 3D active vision: alcuni risultati","year":2003,"lang":"it","type":"article","venue":"NPARC","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Active vision; Machine vision; Construct (python library); High resolution","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001122435,0.0006763376,0.0007146191,0.0002385515,0.000554817,0.0006212027,0.001566143,0.0004037087,0.001906978],"category_scores_gemma":[0.0006412431,0.0006164393,0.0002820407,0.001004226,0.0003921059,0.001388789,0.0005804221,0.0007206012,0.0008137106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000295225,"about_ca_system_score_gemma":0.0002979418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002264331,"about_ca_topic_score_gemma":0.00000768505,"domain_scores_codex":[0.994523,0.0007000414,0.0009194531,0.001311359,0.001431185,0.001114964],"domain_scores_gemma":[0.9964784,0.0004286723,0.000375331,0.00140956,0.0007842782,0.00052371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006036402,0.004240225,0.001769741,0.0003426724,0.0006068607,0.0001733993,0.006413198,0.0001412822,0.2343501,0.520937,0.03619456,0.1942273],"study_design_scores_gemma":[0.005771028,0.00980892,0.01001251,0.003663274,0.000652573,0.000159387,0.00101131,0.09920131,0.6047747,0.08337442,0.1763272,0.005243462],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02813584,0.0008456042,0.2738061,0.003063002,0.002069638,0.001763862,0.000043895,0.0009180127,0.6893541],"genre_scores_gemma":[0.9603871,0.0004153636,0.03344086,0.0003428865,0.0001982504,0.00009065161,0.000009680435,0.00005611205,0.005059084],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9322513,"threshold_uncertainty_score":0.9999643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03245937128017858,"score_gpt":0.282795567920565,"score_spread":0.2503361966403864,"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."}}