{"id":"W3152619636","doi":"10.1109/infocom42981.2021.9488739","title":"VideoLoc: Video-based Indoor Localization with Text Information","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Discriminative model; Artificial intelligence; Cluster analysis; Frame (networking); Automatic summarization; Software deployment; Computer vision; Set (abstract data type); Key (lock); Centroid; Pattern recognition (psychology); Data mining","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":[0.0001046217,0.0001043226,0.000103432,0.00009287707,0.00008768082,0.000194877,0.0002559376,0.00004859781,0.00005959396],"category_scores_gemma":[0.0001007359,0.00008113607,0.00002805933,0.0008227433,0.00003017307,0.002716032,0.00008939501,0.00007873187,0.00006871676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000382894,"about_ca_system_score_gemma":0.0001650888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001079493,"about_ca_topic_score_gemma":0.000008305154,"domain_scores_codex":[0.9991731,0.00003220474,0.0001949385,0.0001817978,0.0002548075,0.0001631722],"domain_scores_gemma":[0.9990203,0.00005196368,0.00007900353,0.0004131937,0.0003771591,0.00005838103],"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":[0.00007615447,0.0001698729,0.004818252,0.0001150657,0.00003057711,0.0000893506,0.0004395789,0.003189737,0.00184397,0.1704896,0.01017718,0.8085607],"study_design_scores_gemma":[0.0006848206,0.0002120237,0.0007436278,0.00005917078,0.000006090958,0.0000333587,0.00004617912,0.1228666,0.7674204,0.004388323,0.1032295,0.0003099351],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001846514,0.00004067236,0.9922682,0.0008639886,0.00003861518,0.0001194653,8.177847e-7,0.0005156437,0.005967962],"genre_scores_gemma":[0.4896635,0.00002091319,0.5025286,0.007387976,0.00002161337,0.00002285604,0.00003044946,0.000007878965,0.0003161785],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8082507,"threshold_uncertainty_score":0.3308633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006651350488567215,"score_gpt":0.2316458125230128,"score_spread":0.2249944620344455,"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."}}