{"id":"W1984104679","doi":"10.1117/12.389348","title":"<title>Integrated radar-photometry sensor based on constrained optical flow</title>","year":2000,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Optical flow; Radar; Computer science; Computer vision; Sensor fusion; Remote sensing; Artificial intelligence; Computation; Radar imaging; Radar engineering details; Geology; Algorithm; Telecommunications","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":[0.0003040994,0.0003424743,0.0004482494,0.0005047861,0.0001705082,0.0007194109,0.000634321,0.0007519395,0.01161124],"category_scores_gemma":[0.0005303065,0.000178142,0.0001182422,0.0004217697,0.0003459294,0.001032197,0.0003803194,0.0003595877,0.00413076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003636955,"about_ca_system_score_gemma":0.0003363653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001456183,"about_ca_topic_score_gemma":0.002011724,"domain_scores_codex":[0.9997594,0.00002759117,0.00001007312,0.0000491576,0.0001360484,0.00001761151],"domain_scores_gemma":[0.999668,0.00004734623,0.0000338295,0.000053966,0.0001663332,0.00003045751],"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":[0.0006836927,0.0001649157,0.001091823,0.000256018,0.00004123906,0.0003617474,0.00005816965,0.01204958,0.4211347,0.01321098,0.04170684,0.5092404],"study_design_scores_gemma":[0.0001336843,0.0004793409,0.005022488,0.00008339672,0.00004339424,0.0007069659,0.00004259513,0.4467807,0.4269633,0.004632127,0.1149901,0.0001218714],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04623188,0.001608513,0.9059843,0.0007416175,0.001009376,0.0002844425,0.0007393874,0.005091435,0.03830895],"genre_scores_gemma":[0.3943838,0.001018035,0.5221338,0.0005638084,0.0004050327,0.0002058523,0.001707462,0.0004739476,0.07910824],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01161124,"threshold_uncertainty_score":0.03884351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009146072984593464,"score_gpt":0.2342558008821855,"score_spread":0.2251097278975921,"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."}}