{"id":"W2099341511","doi":"10.1109/imtc.2005.1604257","title":"Calibration of a Multi-Modal 3D Scanner","year":2006,"lang":"en","type":"article","venue":"2005 IEEE Instrumentationand Measurement Technology Conference Proceedings","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Modal; Calibration; Computer science; Range (aeronautics); Triangulation; Scanner; Quality (philosophy); Artificial intelligence; Computer vision; Engineering; Geography; 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":[0.001363664,0.0004941381,0.0005057896,0.001015955,0.0006225847,0.001105577,0.001009307,0.001247649,0.003030718],"category_scores_gemma":[0.002741694,0.000622211,0.0005627375,0.0008355766,0.0007742277,0.001649338,0.001774081,0.001091105,0.001115682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006496336,"about_ca_system_score_gemma":0.001436914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001238052,"about_ca_topic_score_gemma":0.002826172,"domain_scores_codex":[0.9985396,0.0002075593,0.00005100804,0.0002777583,0.0008478172,0.00007628008],"domain_scores_gemma":[0.9988176,0.0002655204,0.00008807937,0.000400887,0.000372114,0.00005569752],"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":[0.0003297443,0.0001965236,0.009170495,0.0003012991,0.0001185953,0.0003182723,0.000858862,0.0752351,0.5799034,0.01215673,0.004771594,0.3166394],"study_design_scores_gemma":[0.00004734283,0.0003906579,0.01509931,0.00008228053,0.00005266391,0.001670467,0.0005150504,0.664396,0.2778538,0.01067525,0.0289829,0.0002342812],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04662228,0.00007699263,0.9453835,0.0002593043,0.00008250137,0.0001269591,0.0002322359,0.002491466,0.004724749],"genre_scores_gemma":[0.3282296,0.0001098318,0.6682053,0.0003076839,0.00002226672,0.0001879999,0.0003672778,0.0002338628,0.002336092],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003030718,"threshold_uncertainty_score":0.01013875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04120095784445774,"score_gpt":0.2557048600582035,"score_spread":0.2145039022137458,"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."}}