{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001064457,0.00005513972,0.00004713129,0.00005078327,0.00003860761,0.000004465096,0.00007145906,0.00009891403,0.000009562423],"category_scores_gemma":[0.00001618314,0.00005430057,0.00001409708,0.00008135572,0.0000133764,0.00004395788,0.00001149577,0.00006840794,0.00002710915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000451073,"about_ca_system_score_gemma":0.000001702472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.920426e-7,"about_ca_topic_score_gemma":0.000001529336,"domain_scores_codex":[0.9996138,0.000001069499,0.0001234177,0.00006369999,0.00005026158,0.0001477706],"domain_scores_gemma":[0.9998659,0.00003185614,0.0000108979,0.0000679765,0.000007363234,0.00001593917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002308973,0.00003638572,0.02868062,0.0004847178,0.00008580679,0.000004132842,0.0009331173,0.4807561,0.03218869,0.04293513,0.012894,0.4009782],"study_design_scores_gemma":[0.0004859682,0.0000257445,0.009947278,0.00003119129,0.00001002661,0.000003996648,0.0006879279,0.4995484,0.4650692,0.001077617,0.02282184,0.0002908281],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03732787,0.00009084542,0.9607431,0.00001984931,0.0001329178,0.0001151198,6.160438e-7,0.0005373232,0.001032331],"genre_scores_gemma":[0.9969946,0.00001533042,0.002684267,0.00005689936,0.00004532811,0.000002795146,0.000009099425,0.00001284226,0.0001787981],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9596668,"threshold_uncertainty_score":0.2214313,"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."}}