{"id":"W4400737280","doi":"10.1145/3678878","title":"Enabling Technologies and Techniques for Floor Identification","year":2024,"lang":"en","type":"review","venue":"ACM Computing Surveys","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Impact","funders":"","keywords":"Computer science; Identification (biology); Data science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001377481,0.000417342,0.0008640714,0.00060251,0.0001271235,0.0002342651,0.0006643215,0.000623595,0.000001001845],"category_scores_gemma":[0.0009832467,0.0003596429,0.0001878927,0.0006298247,0.00008751484,0.00007159741,0.00038828,0.0004240198,0.00002762074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009410647,"about_ca_system_score_gemma":0.00003015539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004972718,"about_ca_topic_score_gemma":0.000003316706,"domain_scores_codex":[0.9984207,0.00007926195,0.0006363882,0.0004443566,0.00009870601,0.0003206025],"domain_scores_gemma":[0.9987512,0.0003762027,0.0001162561,0.000664363,0.00007392711,0.00001802403],"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":[9.758592e-8,0.00000250322,0.000001079773,0.01612136,0.00007394981,0.000001663354,0.00001868945,0.000009352969,0.000004089493,0.0003471932,0.0007916802,0.9826283],"study_design_scores_gemma":[0.0000534313,0.00002402653,0.000001892347,0.008117545,0.0004573685,0.00002889913,0.0001203486,0.003358354,0.0009134207,0.003022356,0.9831787,0.0007236628],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000005759497,0.8437685,0.1452581,0.00001548901,0.0005517477,0.0006979814,0.00004942702,0.009612948,0.00003995117],"genre_scores_gemma":[0.0006555416,0.9920456,0.00669848,0.000002335115,0.0001065323,0.0001413348,0.0001523367,0.0001313678,0.00006648731],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.982387,"threshold_uncertainty_score":0.9998856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0449923320987422,"score_gpt":0.3235886375988765,"score_spread":0.2785963055001343,"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."}}