{"id":"W6997302011","doi":"","title":"UK Could Capture a Quarter of $750bn Marine Energy Market","year":2011,"lang":"en","type":"other","venue":"","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Energy (signal processing); Marine energy; Economic forecasting; Energy market","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008092738,0.0002382043,0.0002788171,0.00006355354,0.0000219799,0.000004427559,0.000314297,0.0003123851,0.9380603],"category_scores_gemma":[0.000002138625,0.0001757648,0.0001013336,0.0001267098,0.000165793,0.00001668235,0.0001050888,0.0001178069,0.0003612467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001941077,"about_ca_system_score_gemma":0.00001099346,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03574326,"about_ca_topic_score_gemma":0.004942135,"domain_scores_codex":[0.9989129,0.0000180427,0.0002184533,0.000342734,0.0002598597,0.0002480405],"domain_scores_gemma":[0.9993036,0.00000899553,0.0001116289,0.0004463368,0.000003113865,0.0001263617],"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":[0.000009533966,0.00009379793,0.004822116,0.00002349222,0.00001285128,0.0000106829,0.00002761494,9.083597e-7,0.00003392241,0.0003660399,0.9914585,0.003140484],"study_design_scores_gemma":[0.000142821,0.00003565262,0.002947524,0.00003895079,0.00002464377,0.00000424024,0.00001558139,0.00005546345,0.00003672945,0.0001307671,0.996317,0.0002505774],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00001450963,0.00006874744,0.0006176921,0.00003481764,0.00009610046,0.00008927182,0.00003224429,0.00005940603,0.9989872],"genre_scores_gemma":[0.007916591,0.0001217035,0.001562609,0.0001627104,0.00003229459,0.000008985874,0.00003359948,0.0001145602,0.9900469],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9376991,"threshold_uncertainty_score":0.9706778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004529284401599535,"score_gpt":0.1775392805615303,"score_spread":0.1730099961599308,"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."}}