{"id":"W4214557247","doi":"10.3390/s22051784","title":"Calibration of Stereo Pairs Using Speckle Metrology","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Metrology; Speckle pattern; Calibration; Computer vision; Artificial intelligence; Translation (biology); Computer science; Rotation (mathematics); Speckle noise; 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":[0.001133549,0.0005064034,0.0005640239,0.001357533,0.0004376328,0.0007361969,0.0007764846,0.0006401788,0.002165146],"category_scores_gemma":[0.00252477,0.0004035796,0.0003854574,0.001171872,0.0006136438,0.001043284,0.001959243,0.0007993173,0.0008566656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004251062,"about_ca_system_score_gemma":0.0005233969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003739573,"about_ca_topic_score_gemma":0.0005413272,"domain_scores_codex":[0.9978384,0.0003531054,0.00007502513,0.000378214,0.001275952,0.00007922329],"domain_scores_gemma":[0.9988897,0.0002130393,0.0001237377,0.0003849305,0.000359224,0.00002932691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002313172,0.0001034999,0.004252723,0.0002992594,0.00008869219,0.0002052549,0.0005064599,0.02840833,0.4185008,0.02323102,0.002772111,0.5214006],"study_design_scores_gemma":[0.0000945072,0.0004115512,0.008274487,0.0001119782,0.00006420453,0.001745427,0.0002928382,0.3001387,0.6372859,0.01846081,0.03295292,0.0001665772],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03041342,0.0001607338,0.9638712,0.000045699,0.00006222934,0.00007066804,0.0000832384,0.0005839646,0.004708808],"genre_scores_gemma":[0.355134,0.000306708,0.641856,0.0001173542,0.00004762259,0.0001291089,0.000267976,0.0001590919,0.001982076],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002165146,"threshold_uncertainty_score":0.007243097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05940312674680388,"score_gpt":0.2753034664644331,"score_spread":0.2159003397176292,"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."}}