{"id":"W1985490796","doi":"10.1145/1982595.1982614","title":"Selection and execution of user level test cases for energy cost evaluation of smartphones","year":2011,"lang":"en","type":"article","venue":"","topic":"Green IT and Sustainability","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Test (biology); Selection (genetic algorithm); Energy (signal processing); Work (physics); Scenario testing; Embedded system; Engineering; Machine learning; 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":[0.005854208,0.00176995,0.0008666579,0.00244582,0.0003898002,0.001091178,0.001793673,0.0008625769,0.00127439],"category_scores_gemma":[0.03992523,0.0004671657,0.0007592729,0.0009843694,0.0005293609,0.001212113,0.0007425499,0.000714404,0.0004241576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006963584,"about_ca_system_score_gemma":0.0006839503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001769936,"about_ca_topic_score_gemma":0.002405996,"domain_scores_codex":[0.9899047,0.004857877,0.001285402,0.0008620924,0.002437082,0.0006528132],"domain_scores_gemma":[0.9451866,0.03700466,0.004111719,0.005081631,0.007633125,0.0009822765],"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":[0.004256918,0.007782948,0.1898088,0.001423654,0.0008363284,0.004533579,0.002084752,0.1590045,0.2246651,0.00405596,0.006550865,0.3949966],"study_design_scores_gemma":[0.0006127054,0.006933185,0.0717421,0.0001935884,0.0003403007,0.001783853,0.001314261,0.5851198,0.3229073,0.002575483,0.006242095,0.0002352727],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8786995,0.0001748698,0.1150453,0.000182085,0.0000435045,0.001171334,0.0006541507,0.002636259,0.00139306],"genre_scores_gemma":[0.9098251,0.00008277369,0.08713078,0.00008587458,0.00001162989,0.001123312,0.0009625534,0.0002524993,0.0005253527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005854208,"threshold_uncertainty_score":0.03096038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09590530263328696,"score_gpt":0.2634202754029892,"score_spread":0.1675149727697023,"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."}}