{"id":"W1995872126","doi":"10.1145/2814189.2817271","title":"ModeSens: an approach for multi-modal mobile sensing","year":2015,"lang":"en","type":"article","venue":"","topic":"Green IT and Sustainability","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Computer science; Modal; Modularity (biology); Energy consumption; Distributed computing; Resource (disambiguation); Engineering; Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001983205,0.00009543215,0.0001134188,0.00003006202,0.00002890202,0.00002566037,0.00005883498,0.00006360515,0.00000300645],"category_scores_gemma":[0.00002517587,0.00008580954,0.00003818875,0.00005513204,0.0000184569,0.0001390076,0.00001422327,0.00005876159,0.000003403124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007908457,"about_ca_system_score_gemma":0.00001923532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006728636,"about_ca_topic_score_gemma":0.0000207009,"domain_scores_codex":[0.9994493,0.00001221892,0.0001044916,0.0001400334,0.00007227507,0.0002216809],"domain_scores_gemma":[0.9995433,0.00001160511,0.000005668839,0.0002094068,0.0001020311,0.0001279896],"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":[0.00004355893,0.000208007,0.001694742,0.0002822799,0.00004328996,0.000004998201,0.00384257,0.9472162,0.001736336,0.001108569,0.002115575,0.04170385],"study_design_scores_gemma":[0.0004014475,0.00003438158,0.00009620527,6.867947e-7,0.000004659696,0.000002824194,0.00258127,0.9948999,0.0007707687,0.0003577339,0.0007239311,0.0001261698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3954616,0.00002819424,0.6001423,0.000003294666,0.00006355403,0.0003107618,0.000002693585,0.0003200386,0.003667573],"genre_scores_gemma":[0.8019506,2.547323e-7,0.1975795,0.000009540925,0.00005499036,0.00001958965,0.00001412772,0.00002051694,0.000350949],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.406489,"threshold_uncertainty_score":0.3499212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07176409355263703,"score_gpt":0.2878816126548875,"score_spread":0.2161175191022505,"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."}}