{"id":"W7048571682","doi":"","title":"A linear regression model for marine propeller optimization, prototyping and design","year":2006,"lang":"en","type":"article","venue":"NPARC","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada; Transport Canada","keywords":"Polynomial regression; Propeller; Linear regression; Interpolation (computer graphics); Proper linear model; Linear model; Polynomial; Regression analysis; Linear interpolation","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00267413,0.001499988,0.0009613471,0.0009800773,0.000460892,0.000991856,0.001873699,0.001151357,0.009379967],"category_scores_gemma":[0.006267909,0.0007617856,0.00170297,0.001317416,0.0004661873,0.001036358,0.0007236883,0.00215124,0.006121272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009336412,"about_ca_system_score_gemma":0.001951059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00475511,"about_ca_topic_score_gemma":0.00467236,"domain_scores_codex":[0.9975861,0.0007489405,0.0001309924,0.0003972799,0.001028767,0.0001078508],"domain_scores_gemma":[0.9973537,0.001240906,0.0002580266,0.0002497933,0.0008611884,0.00003654371],"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":[0.0001090881,0.000106328,0.00108379,0.0003267862,0.00007529142,0.00009716247,0.00008162618,0.8018754,0.0103626,0.02159942,0.004931845,0.1593508],"study_design_scores_gemma":[0.00001468262,0.0001018618,0.000310392,0.00001745218,0.00002181825,0.000054942,0.000009888274,0.9837376,0.003973432,0.00314815,0.008583322,0.00002657308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001064554,0.00004449493,0.9969363,0.00003619196,0.00001824519,0.00005391084,0.00008602064,0.0007619916,0.0009982815],"genre_scores_gemma":[0.1479999,0.0004923451,0.8305216,0.0001329485,0.00008349529,0.001619506,0.00109124,0.0008765047,0.01718249],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009379967,"threshold_uncertainty_score":0.03137904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02548010798068618,"score_gpt":0.2679378702741337,"score_spread":0.2424577622934475,"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."}}