{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.3193828,0.001456085,0.002453107,0.007887259,0.00393377,0.01404303,0.008269669,0.005426254,0.008166377],"category_scores_gemma":[0.6344935,0.002197763,0.002732376,0.01367407,0.00951456,0.01608652,0.01644653,0.004930196,0.004901155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00511659,"about_ca_system_score_gemma":0.0139397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005720149,"about_ca_topic_score_gemma":0.002797853,"domain_scores_codex":[0.5240549,0.3113417,0.05663015,0.04722039,0.05667247,0.004080409],"domain_scores_gemma":[0.2436641,0.418589,0.05222309,0.2064164,0.07654744,0.002560108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004088992,0.0007111887,0.1081472,0.006929163,0.001641482,0.000987384,0.01704434,0.03040042,0.005075459,0.125454,0.04357699,0.6559435],"study_design_scores_gemma":[0.001929685,0.001526552,0.08907412,0.009890532,0.0009943078,0.00169811,0.009657942,0.05160734,0.02449041,0.4459527,0.362293,0.000885367],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.1024573,0.008418471,0.7660254,0.02155809,0.002714132,0.01357796,0.01979036,0.007557554,0.05790077],"genre_scores_gemma":[0.4876455,0.002417371,0.4422061,0.007062919,0.001608616,0.02681539,0.02186652,0.002936939,0.007440649],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.3193828,"threshold_uncertainty_score":0.8393221,"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."}}