{"id":"W6976563327","doi":"10.6068/dp172a5b116c325","title":"TREND: Organisation for Economic Co-operation and Development (OECD). OECD Factbook 2014: Economic, Environmental and Social Statistics: Public Finance - Government Support for Fishing | Country: Australia | Socioeconomic Indicator: Government Financial Transfers to Fishing, 2000 - 2012. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 062-001-088","year":2020,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Fishing; Revenue; Government revenue; Public finance; Socioeconomic status; Economic data; Socioeconomic development","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00243512,0.001902817,0.002559513,0.008243018,0.0008332446,0.004074762,0.002816497,0.001516497,0.08513135],"category_scores_gemma":[0.02061511,0.001219091,0.001520445,0.02967427,0.0004983176,0.003695475,0.002360206,0.004300017,0.09732334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002998214,"about_ca_system_score_gemma":0.01046299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1045121,"about_ca_topic_score_gemma":0.05830025,"domain_scores_codex":[0.9964575,0.0004523998,0.0006791935,0.0006835543,0.001165538,0.0005617335],"domain_scores_gemma":[0.9858344,0.002150003,0.001675601,0.001129807,0.008601216,0.0006089574],"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":[0.00002145283,0.000009651271,0.0004879968,0.000385659,0.00001957584,0.000007340151,0.00001225351,0.00006511401,0.00001344928,0.0004078231,0.9967353,0.001834504],"study_design_scores_gemma":[0.000109543,0.00001227023,0.008351938,0.001005741,0.00004458859,0.00001742772,0.0001586071,0.000170854,0.0001063136,0.0009062234,0.9890819,0.00003457306],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004444553,0.00005764671,0.00004534864,0.0001234017,0.00005836062,0.00001811203,0.9988028,0.00005752068,0.000792379],"genre_scores_gemma":[0.0003018027,0.0002531892,0.0003195379,0.00009209809,0.00002665652,0.0002394694,0.9969536,0.0000986352,0.001714954],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1045121,"threshold_uncertainty_score":0.2847927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02728047574520488,"score_gpt":0.2567684780303536,"score_spread":0.2294880022851487,"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."}}