{"id":"W2077684077","doi":"10.1109/epec.2013.6802962","title":"Open-loop maximum power point tracking strategy for Marine Current Turbines based on resource prediction","year":2013,"lang":"en","type":"article","venue":"","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Control theory (sociology); Maximum power point tracking; Computer science; Operating point; Maximum power principle; Predictability; Variable (mathematics); Engineering; Voltage; Electronic engineering; Mathematics; Artificial intelligence","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":[0.0001869183,0.0003760407,0.0003754853,0.0002072043,0.0002896324,0.0003808522,0.0006445457,0.0003585245,0.001006009],"category_scores_gemma":[0.0005478439,0.0001745187,0.0001900348,0.0001680586,0.0002848135,0.0004840481,0.0003251049,0.0004099014,0.0002283995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002966255,"about_ca_system_score_gemma":0.0002743168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001657711,"about_ca_topic_score_gemma":0.00182389,"domain_scores_codex":[0.9998775,0.00001834105,0.000006448792,0.0000293976,0.00005786928,0.0000104747],"domain_scores_gemma":[0.999827,0.00007251405,0.00003834064,0.00001393023,0.00003844404,0.00000976262],"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":[0.0001772939,0.0001016158,0.001176683,0.0001212254,0.00003588321,0.0002228771,0.0001920786,0.7418213,0.03465473,0.01362106,0.001561479,0.2063138],"study_design_scores_gemma":[0.00001362655,0.0000755271,0.0001816392,0.000004900234,0.000006376122,0.00003006441,0.000007374385,0.9945022,0.002787711,0.00174348,0.0006411102,0.000005969738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02747081,0.00009590806,0.9682655,0.00007041177,0.00002299764,0.00003975595,0.00001413112,0.0003578073,0.003662696],"genre_scores_gemma":[0.9503379,0.00006058691,0.04783048,0.00003209172,0.00001450714,0.00005364898,0.00001988118,0.00001710129,0.001633712],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001657711,"threshold_uncertainty_score":0.003365457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02928171671259657,"score_gpt":0.2606745077063002,"score_spread":0.2313927909937037,"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."}}