{"id":"W2162583946","doi":"10.1007/978-3-540-75696-5_12","title":"GlobeCon – A Scalable Framework for Context Aware Computing","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Scalability; Context (archaeology); Context model; Distributed computing; Ubiquitous computing; Context management; Server; Directory; Key (lock); Context awareness; World Wide Web; Database; Human–computer interaction; Computer security; Artificial intelligence; Operating system; Object (grammar); Geography","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002395613,0.0008423976,0.001116659,0.001178502,0.0005615145,0.001181865,0.003957732,0.0008192124,0.00003706868],"category_scores_gemma":[0.0004066043,0.000858905,0.0003646373,0.0009255586,0.0006344356,0.0009409994,0.00153247,0.00126645,0.0001332556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007143127,"about_ca_system_score_gemma":0.0008334855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007999311,"about_ca_topic_score_gemma":0.000349674,"domain_scores_codex":[0.9938677,0.00006025235,0.001044097,0.002473927,0.001250787,0.001303253],"domain_scores_gemma":[0.9923754,0.00384321,0.0007498895,0.00182673,0.0008595225,0.0003452591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001296869,0.00004150406,0.0000675308,0.00009927535,0.00002511176,0.00004827481,0.0006013879,0.00112894,0.00001940216,0.03565494,0.00006999655,0.9622307],"study_design_scores_gemma":[0.0009263042,0.0004140756,0.00009180433,0.002985962,0.00002257686,0.0002798302,0.000002317136,0.6422073,0.001773467,0.3332946,0.01609483,0.001906863],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000644279,0.0005874381,0.9896855,0.0007802779,0.004647947,0.001370199,0.00002646022,0.0004376888,0.002400039],"genre_scores_gemma":[0.4171119,0.00001281783,0.576515,0.004240413,0.001516392,0.00002674547,0.00001291337,0.00008912022,0.0004747199],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9603238,"threshold_uncertainty_score":0.999855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04642367522695427,"score_gpt":0.2992256377696307,"score_spread":0.2528019625426765,"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."}}