{"id":"W2093817806","doi":"10.1007/s00138-003-0129-y","title":"Low-cost interactive active range finder","year":2003,"lang":"en","type":"article","venue":"Machine Vision and Applications","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Laser pointer; Computer vision; Computer science; Artificial intelligence; Laser; Computer graphics (images); Interactivity; Range (aeronautics); Triangulation; Rendering (computer graphics); Object (grammar); Optics; Engineering; Physics; Mathematics; Multimedia","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000274441,0.00009446629,0.00009297015,0.00003405673,0.0001450923,0.00002481061,0.00005855001,0.00002567299,0.0001685736],"category_scores_gemma":[0.00001305157,0.00007540985,0.00002892857,0.0001318325,0.00007035609,0.00007360961,0.00004427353,0.0001533778,0.00005899795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000112174,"about_ca_system_score_gemma":0.000005934126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000121713,"about_ca_topic_score_gemma":0.000001901096,"domain_scores_codex":[0.9995452,0.00001461172,0.00008800372,0.0001901497,0.00004856207,0.0001134907],"domain_scores_gemma":[0.9996139,0.00008998951,0.00004111067,0.0001810476,0.00002951718,0.00004439904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009899796,0.000192331,0.001843529,0.000002308286,0.00001773797,2.178836e-7,0.00005410043,0.00002940248,0.001144231,0.3450872,0.0002297593,0.6513892],"study_design_scores_gemma":[0.00200974,0.00009329453,0.01694383,0.00005224276,0.00005788571,0.000005312921,0.001376882,0.004241598,0.0634698,0.3924908,0.5184773,0.0007813444],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05198119,0.00004844785,0.8915574,0.0009572176,0.00003778589,0.0007953777,0.00008223873,0.0001925667,0.05434779],"genre_scores_gemma":[0.9946505,0.000004486346,0.004868807,0.00006776377,0.00002273457,0.0001015722,0.00001928744,0.000009219947,0.0002556303],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9426693,"threshold_uncertainty_score":0.3075124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007016394987284401,"score_gpt":0.2933182687609919,"score_spread":0.2863018737737075,"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."}}