{"id":"W2911540731","doi":"10.2172/1491572","title":"Data Transferability and Collection Consistency in Marine Renewable Energy","year":2018,"lang":"en","type":"report","venue":"","topic":"Marine and Offshore Engineering Studies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Pacific Northwest National Laboratory; Offshore Energy Research Association; Water Power Technologies Office; University College Cork; U.S. Department of Energy","keywords":"Baseline (sea); Process (computing); Data collection; Timeline; Marine energy; Computer science; Renewable energy; Consistency (knowledge bases); Risk analysis (engineering); Environmental science; Environmental resource management; Business; Engineering; Geography; Electrical engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003958958,0.000287614,0.0005199398,0.0001883029,0.00004104364,0.00002589107,0.0001742482,0.0002272664,0.0003369545],"category_scores_gemma":[0.0001130322,0.0002781747,0.00003301765,0.0002290581,0.00005275233,0.00008104787,0.000224412,0.0001879031,0.000001818065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001657846,"about_ca_system_score_gemma":0.0001327269,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01441908,"about_ca_topic_score_gemma":0.1069675,"domain_scores_codex":[0.9987037,0.00001355057,0.0004122956,0.0004122003,0.000217676,0.0002405394],"domain_scores_gemma":[0.9991071,0.00006607715,0.00001753399,0.0006660112,0.00009262028,0.00005067277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002146322,0.00007155238,0.01767899,0.002740688,0.0005287593,0.00004165632,0.00009542337,0.002429513,0.00004975758,0.00006441627,0.952038,0.02423982],"study_design_scores_gemma":[0.0002835017,0.00005413007,0.01037475,0.0001001096,0.0000793161,0.00004623113,0.00002154717,0.01519079,0.0001532775,0.0002191814,0.9729356,0.0005416203],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.002190835,0.002450729,0.003614569,0.00004399406,0.001855008,0.0002233978,0.0001349767,0.0005349593,0.9889515],"genre_scores_gemma":[0.5526104,0.1742545,0.01127586,0.00008412736,0.003593405,0.0003516113,0.004562276,0.0005886994,0.2526791],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7362724,"threshold_uncertainty_score":0.999967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03436430246676429,"score_gpt":0.2476113706396901,"score_spread":0.2132470681729258,"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."}}