{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003322221,0.0001406798,0.0002222555,0.0001421613,0.0001901733,0.00001536622,0.00009216573,0.00004756353,0.00004893861],"category_scores_gemma":[0.00001182461,0.0001499297,0.0001017347,0.0001474705,0.00005325819,0.00005856208,0.00007821211,0.00007858476,2.405613e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003804116,"about_ca_system_score_gemma":0.00006820064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007591789,"about_ca_topic_score_gemma":0.00003836578,"domain_scores_codex":[0.9990594,0.00007124503,0.0002257201,0.0002532613,0.0001432764,0.000247065],"domain_scores_gemma":[0.9993388,0.00004875049,0.00002890416,0.0003508479,0.0001409155,0.00009179729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008867622,0.0003471709,0.0009725684,0.00252113,0.001842657,0.00005101723,0.00494207,0.2566554,0.00008527179,0.3528306,0.005912217,0.3737511],"study_design_scores_gemma":[0.0002495243,0.000083142,0.0009160124,0.000001084367,0.0001769458,0.000006302035,0.006048604,0.05028528,0.000111979,0.007557786,0.9342607,0.0003026567],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6651413,0.2046048,0.0999532,0.007027371,0.001419567,0.004718862,0.00139586,0.002091504,0.01364757],"genre_scores_gemma":[0.9960063,0.001001706,0.0001640678,0.00006050828,0.0001811645,0.001636174,0.0002057266,0.00002539777,0.0007189596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9283485,"threshold_uncertainty_score":0.6113955,"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."}}