{"id":"W4294168589","doi":"10.3390/su141710912","title":"Linear Permanent Magnet Vernier Generators for Wave Energy Applications: Analysis, Challenges, and Opportunities","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Wave and Wind Energy Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Canada","keywords":"Vernier scale; Magnet; Renewable energy; Computer science; Power (physics); Energy (signal processing); Electronic engineering; Engineering; Mechanical engineering; Electrical engineering; Physics; Optics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0002886835,0.0003236314,0.0002508221,0.0004606617,0.0001593945,0.000665182,0.000463624,0.0004609999,0.002483115],"category_scores_gemma":[0.0004237306,0.0001751809,0.0002591533,0.0004930912,0.0003472094,0.00107958,0.000221144,0.0003891404,0.0005713119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001933481,"about_ca_system_score_gemma":0.0001621399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000128869,"about_ca_topic_score_gemma":0.0002651216,"domain_scores_codex":[0.9998753,0.00002384043,0.000005713736,0.00001572568,0.00007027945,0.000009078895],"domain_scores_gemma":[0.9998299,0.00006935651,0.00002857286,0.00001936455,0.00004435033,0.000008396257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002554647,0.0001069333,0.002929514,0.002046279,0.00005324226,0.0007568254,0.0002935642,0.07490052,0.2389468,0.06411895,0.005693947,0.6098979],"study_design_scores_gemma":[0.00006448003,0.001824451,0.007045982,0.0003834535,0.0001404396,0.002342925,0.0004177339,0.6344382,0.1345112,0.03136816,0.1873542,0.0001088403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1813079,0.05253463,0.6999548,0.002200962,0.0005051429,0.0001924636,0.0001934586,0.001029951,0.06208058],"genre_scores_gemma":[0.9005271,0.01840928,0.0677388,0.0001246724,0.0002237152,0.00007804568,0.0001704788,0.00007682206,0.01265115],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002483115,"threshold_uncertainty_score":0.008306921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03049328704547401,"score_gpt":0.2257070711483931,"score_spread":0.195213784102919,"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."}}