{"id":"W2067053438","doi":"10.1145/2750858.2807540","title":"IDyLL","year":2015,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Council","keywords":"Idyll; Inertial measurement unit; Computer science; Computer vision; Dead reckoning; Silhouette; Artificial intelligence; Ambiguity; Geography; Remote sensing; Telecommunications; Global Positioning System; Art","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002013482,0.00002627663,0.0000261089,0.00002279163,0.00000480485,0.000006247711,0.00004303667,0.00002628826,0.00004947556],"category_scores_gemma":[0.00001261026,0.00002191611,0.000006523002,0.00006128351,0.000007299998,0.00003213556,0.000006982019,0.00002198649,0.0002810878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001181393,"about_ca_system_score_gemma":0.000002534965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000211675,"about_ca_topic_score_gemma":0.000002108487,"domain_scores_codex":[0.99985,9.023024e-7,0.00003432822,0.00002341709,0.00003507285,0.00005626255],"domain_scores_gemma":[0.999902,0.000002118143,0.00000135929,0.0000624259,0.00001248495,0.00001964555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003100505,0.00001429337,0.00404127,0.00002564842,0.00002590303,0.00001146152,0.0005483548,0.06205607,0.001076084,0.1986849,0.68119,0.05232291],"study_design_scores_gemma":[0.0006002346,0.00003923622,0.0004144916,0.000005111569,0.000005331302,0.00001042952,0.00114287,0.145313,0.2141077,0.01754654,0.6204609,0.0003541647],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02715862,0.0001853119,0.2132624,0.000101658,0.0004095582,0.00004131386,6.740218e-7,0.00432393,0.7545165],"genre_scores_gemma":[0.9978832,0.000005031833,0.001304595,0.00004061064,0.00001555815,0.000001828514,9.291562e-7,0.000005404368,0.0007428576],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9707246,"threshold_uncertainty_score":0.3612908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02202308815002312,"score_gpt":0.1954120001626369,"score_spread":0.1733889120126137,"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."}}