{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008422173,0.0008085481,0.0005711784,0.001167858,0.0006934557,0.001650412,0.001343941,0.001056417,0.06221528],"category_scores_gemma":[0.002201595,0.0002635166,0.0004366731,0.001028707,0.0003444991,0.001530774,0.003327578,0.0009012247,0.06286917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008155055,"about_ca_system_score_gemma":0.001218744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002224666,"about_ca_topic_score_gemma":0.002637918,"domain_scores_codex":[0.9991322,0.0001332216,0.00005451919,0.0002101586,0.0003429909,0.0001268608],"domain_scores_gemma":[0.9987898,0.0001406785,0.00007228232,0.0004071045,0.0004252723,0.0001648545],"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":[0.0004791568,0.0000895202,0.004225426,0.0004857794,0.00003582787,0.000352765,0.0002627374,0.002598478,0.01193574,0.02985873,0.2466322,0.7030436],"study_design_scores_gemma":[0.00004041892,0.0001102399,0.001732362,0.00007793774,0.0000194444,0.0006045214,0.00009585391,0.01070198,0.01099289,0.00436587,0.9712155,0.0000429366],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02196516,0.004005398,0.5087124,0.002706139,0.002757539,0.0005073859,0.01687266,0.07556558,0.3669078],"genre_scores_gemma":[0.2335586,0.004002027,0.3152031,0.002648119,0.0007400771,0.0006230894,0.04818688,0.005014513,0.3900236],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9377847,"threshold_uncertainty_score":0,"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."}}