{"id":"W4281712258","doi":"10.1088/1742-6596/2265/4/042071","title":"Using Small Wind Turbine Technology to Design an AntiFrost Fan","year":2022,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Aerodynamics; Rotor (electric); Turbine; Frost (temperature); Noise (video); Turbine blade; Mass flow; Mass flow rate; Structural engineering; Engineering; Computer science; Environmental science; Mechanical engineering; Aerospace engineering; Meteorology; Mechanics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001978104,0.0001180993,0.0002094744,0.0001862871,0.000143951,0.00006337343,0.0003089888,0.00002933065,0.00007553543],"category_scores_gemma":[0.00001733664,0.0001141325,0.00003405238,0.0003944813,0.00003958806,0.0002815619,0.0001078722,0.0003313826,0.000002970434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009681775,"about_ca_system_score_gemma":0.0002366255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005529985,"about_ca_topic_score_gemma":0.00000492038,"domain_scores_codex":[0.9991365,0.00004026817,0.000225151,0.00008937206,0.0002492003,0.0002595147],"domain_scores_gemma":[0.999487,0.0000135292,0.00005872181,0.0001326853,0.0001756286,0.0001324463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001284368,0.00008330873,0.000474404,0.00002389574,0.0001050068,0.0001227701,0.00132632,0.4822097,0.4542986,0.004659694,0.0003109695,0.05625697],"study_design_scores_gemma":[0.0005458802,0.001425975,0.001112974,0.00006520176,0.00002154056,0.0003376424,0.003079588,0.006690019,0.9643455,0.01567285,0.006232507,0.0004703546],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7884781,0.00007345877,0.2104581,0.0002542984,0.000324739,0.00007908537,0.000009788487,0.00005198364,0.0002704133],"genre_scores_gemma":[0.9752681,0.00001941709,0.02446534,0.00002794357,0.0001298611,0.000003106431,0.000002569011,0.00001988081,0.00006380831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5100469,"threshold_uncertainty_score":0.4654189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06905804223156495,"score_gpt":0.2770140810980833,"score_spread":0.2079560388665183,"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."}}