{"id":"W1515196472","doi":"10.5220/0003031200890094","title":"A QUALITY OF CONTEXT DRIVEN APPROACH FOR THE SELECTION OF CONTEXT SERVICES","year":2010,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Athabasca University","funders":"","keywords":"Context management; Context (archaeology); Computer science; Mobile computing; Context awareness; Ubiquitous computing; Context model; Process (computing); Services computing; Adaptation (eye); Quality (philosophy); World Wide Web; Computer network; Web service; Human–computer interaction; Artificial intelligence","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":[0.004440388,0.001121977,0.001426492,0.002410243,0.00124886,0.003236069,0.002418502,0.00148561,0.001840406],"category_scores_gemma":[0.01036804,0.0005515739,0.001045919,0.001805233,0.001015433,0.002602047,0.001852422,0.00199105,0.0007000117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001764672,"about_ca_system_score_gemma":0.002409276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00665043,"about_ca_topic_score_gemma":0.00684208,"domain_scores_codex":[0.9959717,0.001133517,0.0003714913,0.0006061154,0.001656843,0.0002602761],"domain_scores_gemma":[0.996503,0.001251035,0.0003170871,0.0003778417,0.001333583,0.0002175441],"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":[0.0006200301,0.0005040169,0.005502295,0.0005668444,0.0002471316,0.0005226579,0.00101024,0.160619,0.033078,0.1179029,0.007334967,0.6720919],"study_design_scores_gemma":[0.00007887218,0.0001876716,0.001042994,0.00006986116,0.0001026776,0.0003550637,0.0001697837,0.9543246,0.009908322,0.02054292,0.01312637,0.00009087081],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00287983,0.0002919543,0.9950501,0.0001691014,0.00004707371,0.0002500887,0.00003601351,0.0003791434,0.0008967252],"genre_scores_gemma":[0.1942725,0.000434348,0.8030569,0.000206421,0.000082526,0.0003350222,0.000158533,0.00008900013,0.001364783],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00665043,"threshold_uncertainty_score":0.02348328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04896230609692102,"score_gpt":0.2994241316366767,"score_spread":0.2504618255397557,"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."}}