{"id":"W1984241264","doi":"10.1145/1577504.1577505","title":"Location aware computing for academic environments","year":2007,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Terminal (telecommunication); Software deployment; Wireless; Wireless network; Mobile computing; Context (archaeology); Ubiquitous computing; Wireless site survey; Point (geometry); Field (mathematics); Location-based service; Computer network; Distributed computing; Wi-Fi array; Telecommunications; Geography; Human–computer interaction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007004213,0.000425832,0.0004593597,0.0008705478,0.001228844,0.00373321,0.001024602,0.001198096,0.01051182],"category_scores_gemma":[0.002681521,0.0002587565,0.0003368945,0.001896662,0.0007645134,0.004622527,0.002442011,0.001207164,0.006749796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008888071,"about_ca_system_score_gemma":0.001139532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001407277,"about_ca_topic_score_gemma":0.00224887,"domain_scores_codex":[0.9993389,0.0002036875,0.00005196163,0.00009571142,0.0002344849,0.00007521781],"domain_scores_gemma":[0.9992366,0.0001621472,0.00006263822,0.0002607359,0.0001686363,0.0001092205],"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":[0.00008641884,0.00007054626,0.0007914456,0.0003213751,0.00002372974,0.0002380312,0.0004548352,0.0117328,0.003589428,0.4533888,0.07375678,0.4555457],"study_design_scores_gemma":[0.00002742285,0.0000536897,0.0007209604,0.0001966256,0.00003070675,0.0003818098,0.0005745616,0.07446837,0.002813776,0.355148,0.5655318,0.00005231455],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009703846,0.01230339,0.8318242,0.01575816,0.001780399,0.0001983828,0.0004708422,0.006583822,0.121377],"genre_scores_gemma":[0.3370928,0.01676897,0.5694936,0.00160214,0.001414972,0.0004088619,0.001169019,0.0006138523,0.07143571],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01051182,"threshold_uncertainty_score":0.03516555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01207576272289978,"score_gpt":0.2469276280809694,"score_spread":0.2348518653580696,"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."}}