{"id":"W3154065259","doi":"10.1145/3434770.3459729","title":"Snowflakes at the Edge","year":2021,"lang":"en","type":"article","venue":"","topic":"Green IT and Sustainability","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Power consumption; Snowflake; Computer science; Perspective (graphical); Edge computing; Focus (optics); Power (physics); Stability (learning theory); Telecommunications; Artificial intelligence; Machine learning; Geography; Physics","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":[0.0009704035,0.0002764698,0.0003914178,0.0005494113,0.0009051973,0.001608476,0.0006220514,0.0004401122,0.002735617],"category_scores_gemma":[0.005124493,0.0001745899,0.0003011154,0.0007968663,0.00102027,0.002019339,0.001251243,0.0007417956,0.0005662056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006267178,"about_ca_system_score_gemma":0.0005338007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005903956,"about_ca_topic_score_gemma":0.006959365,"domain_scores_codex":[0.9991754,0.0001251868,0.00002718876,0.0002605576,0.000273334,0.0001382957],"domain_scores_gemma":[0.9972773,0.001034358,0.0004290017,0.000575226,0.0004907609,0.0001933025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001843154,0.0003635306,0.3549126,0.0004909016,0.0005109698,0.002729374,0.00558079,0.1394394,0.05462881,0.1018802,0.04254607,0.2950741],"study_design_scores_gemma":[0.00008664606,0.0009718017,0.4100384,0.0002662198,0.0002177313,0.00155088,0.006215825,0.2788865,0.02979648,0.1374674,0.1342834,0.0002187507],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9158947,0.0006471334,0.05257436,0.001121452,0.0001725744,0.00006117568,0.001583562,0.0009300113,0.02701496],"genre_scores_gemma":[0.9910675,0.0001107281,0.00512286,0.0002331229,0.00004038186,0.0000217239,0.0006086539,0.0002267516,0.00256822],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.005903956,"threshold_uncertainty_score":0.01173919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005859445578808401,"score_gpt":0.1870477806108664,"score_spread":0.181188335032058,"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."}}