{"id":"W3098846161","doi":"","title":"Simple Subroutine for Inhomogeneous Deployment","year":2014,"lang":"en","type":"preprint","venue":"SOURCE Sheridan's Institutional Repository (Sheridan College)","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Software deployment; Computer science; Simple (philosophy); Subroutine; Cluster analysis; Inference; Distributed computing; Wireless network; Wireless; Algorithm; Artificial intelligence; Programming language; Telecommunications; Software engineering","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":[0.0009187768,0.00270688,0.001188201,0.0011487,0.0006571083,0.001666019,0.003104787,0.002175124,0.1977416],"category_scores_gemma":[0.004895375,0.00128373,0.001542573,0.0006957292,0.0006053076,0.002556881,0.003165346,0.00276872,0.09347016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008666281,"about_ca_system_score_gemma":0.001064493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001342927,"about_ca_topic_score_gemma":0.001406875,"domain_scores_codex":[0.9994357,0.00008295803,0.0000568207,0.0001718452,0.0001609016,0.00009164411],"domain_scores_gemma":[0.9978501,0.001198855,0.00009537418,0.0004240726,0.0002923355,0.000139282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001005892,0.0005610974,0.0062232,0.002082555,0.0002550106,0.001541365,0.0007488015,0.02231486,0.01645178,0.05806798,0.5001711,0.3905763],"study_design_scores_gemma":[0.0007469864,0.0001609721,0.002605291,0.0003623562,0.0000640058,0.001509945,0.0001759043,0.1967001,0.03789623,0.08541991,0.674187,0.000171366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002127443,0.0001120166,0.7347118,0.0002065588,0.000165144,0.0003053615,0.008713845,0.2433396,0.01031828],"genre_scores_gemma":[0.05839454,0.0003741476,0.6924475,0.0010073,0.000235041,0.00271782,0.02430957,0.1738618,0.04665223],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1977416,"threshold_uncertainty_score":0.6615117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01451019806284535,"score_gpt":0.2208868154455066,"score_spread":0.2063766173826613,"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."}}