{"id":"W2564296266","doi":"10.1109/crv.2016.56","title":"Tiny People Finder: Long-Range Outdoor HRI by Periodicity Detection","year":2016,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer vision; Artificial intelligence; Computer science; Pixel; Robustness (evolution); False positive paradox; Robot; Mobile robot","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":[0.0002113221,0.0003788404,0.0005092819,0.0009929892,0.0001873403,0.0003446905,0.0005937747,0.0003355978,0.001241789],"category_scores_gemma":[0.0004597527,0.0002143391,0.000262521,0.0005920812,0.000217703,0.0004400677,0.00043709,0.0003240077,0.0009760332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001215814,"about_ca_system_score_gemma":0.0001750255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000844134,"about_ca_topic_score_gemma":0.001772067,"domain_scores_codex":[0.9998193,0.00001810469,0.000006985786,0.00006066882,0.0000679758,0.00002700376],"domain_scores_gemma":[0.9997681,0.00004196104,0.00005105701,0.00005932779,0.00004695995,0.00003265922],"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":[0.0003892819,0.0001368913,0.01071339,0.0002019713,0.0001012514,0.0004527619,0.000193334,0.00718736,0.2151682,0.001187771,0.006171538,0.7580962],"study_design_scores_gemma":[0.00008421845,0.0006781479,0.07294275,0.00006393628,0.0001437395,0.003958724,0.0002174399,0.7153789,0.1851392,0.002786405,0.01847424,0.0001323331],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1742013,0.001075164,0.8111284,0.0001020344,0.0001920996,0.0001401571,0.0005959735,0.006323752,0.006241132],"genre_scores_gemma":[0.5512167,0.0003636911,0.4431908,0.0001209868,0.0001219338,0.0001012768,0.0008206695,0.0002908203,0.003773192],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001241789,"threshold_uncertainty_score":0.004154265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01246836281104384,"score_gpt":0.2497002429913455,"score_spread":0.2372318801803017,"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."}}