{"id":"W2063554049","doi":"10.1109/tim.2011.2174102","title":"Accurate Measurement of Surface Grid Intersections From Close-Range Video Sequences","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Nvidia","keywords":"Intersection (aeronautics); Grid; Subpixel rendering; Computer science; Computer vision; Computer graphics (images); Ridge; Artificial intelligence; Frame rate; Range (aeronautics); Geometry; Pixel; Geology; Mathematics; Engineering","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":[0.0002200988,0.0004556174,0.0004712253,0.001116768,0.000349009,0.0006474075,0.0006746391,0.0004800958,0.001197201],"category_scores_gemma":[0.001236201,0.0002821898,0.0001318465,0.0007289678,0.0002240503,0.0006991852,0.0004963677,0.0005853165,0.0006519666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003062927,"about_ca_system_score_gemma":0.0003605692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001180171,"about_ca_topic_score_gemma":0.002163329,"domain_scores_codex":[0.9996112,0.00003229208,0.00001715768,0.00007716046,0.0002251507,0.00003715853],"domain_scores_gemma":[0.9993925,0.0001252823,0.0001073511,0.000085199,0.0002545475,0.00003511852],"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":[0.0001649666,0.00007837944,0.002399178,0.0001679952,0.00001788316,0.0002838625,0.0001173943,0.005783357,0.7752203,0.001051556,0.0008152268,0.2138999],"study_design_scores_gemma":[0.00002339611,0.0002400325,0.01397085,0.00004021642,0.00002081158,0.001517448,0.0002245893,0.2333053,0.7435946,0.001312174,0.00569377,0.0000568943],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2000587,0.0003894973,0.7937078,0.00008592541,0.00006092083,0.0001314985,0.0003992897,0.002482613,0.002683832],"genre_scores_gemma":[0.4257246,0.0003926361,0.5718729,0.00002921665,0.00002553864,0.0001044455,0.0006332778,0.0001557151,0.001061715],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001197201,"threshold_uncertainty_score":0.004005015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08187591031287196,"score_gpt":0.2854324639176327,"score_spread":0.2035565536047607,"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."}}