{"id":"W2081442688","doi":"10.1002/cvde.200806741","title":"Planar Source Line‐of‐Sight Model with Automatically Adjusting Time Increment and Local Sticking Factors","year":2009,"lang":"en","type":"article","venue":"Chemical Vapor Deposition","topic":"Plasma Diagnostics and Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Planar; Plane (geometry); Line-of-sight; Line (geometry); Line source; Deposition (geology); Feature (linguistics); Flux (metallurgy); Process (computing); Mechanics; Scale (ratio); Simple (philosophy); Materials science; Geometry; Computational physics; Computer science; Optics; Physics; Mathematics; Geology; Computer graphics (images); Composite material","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":[0.0002921238,0.0004717042,0.0006402755,0.0003755159,0.0003341855,0.0007666145,0.001938703,0.001493647,0.002827439],"category_scores_gemma":[0.0009185234,0.0004528173,0.0006721577,0.0004533683,0.0005024737,0.0008137263,0.0005006741,0.0006922864,0.0004552369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009191897,"about_ca_system_score_gemma":0.001089478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01246863,"about_ca_topic_score_gemma":0.00570476,"domain_scores_codex":[0.9998807,0.00001948662,0.000005253513,0.00002609568,0.00004833898,0.00002011493],"domain_scores_gemma":[0.9997087,0.0001028958,0.00004453249,0.00003913313,0.00007859159,0.0000260908],"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":[0.00002392599,0.00001918522,0.0002125773,0.00001216671,0.000007648977,0.00005082169,0.00001600605,0.9914458,0.002687708,0.003613592,0.0001937816,0.001716794],"study_design_scores_gemma":[0.000005345239,0.000005101679,0.00002467864,6.151601e-7,0.000001591018,0.00000429278,0.000001349376,0.9993259,0.0002705358,0.0002091378,0.0001492732,0.000002217001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1741673,0.000231438,0.8052465,0.0003236708,0.0001020625,0.0001476431,0.000710659,0.001510459,0.01756028],"genre_scores_gemma":[0.8970749,0.0002311611,0.09137826,0.0000880422,0.00002830786,0.0002877944,0.0003994226,0.0002538898,0.01025829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01246863,"threshold_uncertainty_score":0.02479213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006503263152582234,"score_gpt":0.1822549281064474,"score_spread":0.1757516649538652,"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."}}