{"id":"W2596401107","doi":"","title":"Cuentas económicas de Galicia: Tercer trimestre de 2016 [Galicia's economic accounts: 2016 Third quarter]","year":2016,"lang":"es","type":"article","venue":"MPRA Paper","topic":"Finance, Taxation, and Governance","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Dynamism; Unemployment; Economics; Geography; Demographic economics; Economy; Economic growth","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":[0.0003996354,0.0007347454,0.0005824746,0.002509288,0.0004375507,0.00279216,0.0004839469,0.0008016297,0.0102353],"category_scores_gemma":[0.001252981,0.0002308732,0.0003413635,0.009051068,0.0003753846,0.0009783482,0.001190737,0.00105212,0.004978047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003968677,"about_ca_system_score_gemma":0.001554476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07145325,"about_ca_topic_score_gemma":0.04386742,"domain_scores_codex":[0.9997976,0.00001865236,0.00001905773,0.00003504435,0.00007693602,0.00005258363],"domain_scores_gemma":[0.9996924,0.00002825495,0.0001065123,0.0000317879,0.0001095578,0.00003147291],"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":[0.0005185524,0.0000336715,0.01500715,0.00194655,0.00009188957,0.0003693132,0.0005668013,0.002044593,0.0006956025,0.01281664,0.8116694,0.1542398],"study_design_scores_gemma":[0.00002606744,0.000008246353,0.07179273,0.0003657159,0.00001281211,0.00008253532,0.0002173533,0.0002132522,0.0002304824,0.0009256701,0.9261105,0.00001450299],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.08212712,0.2209184,0.001071477,0.02219584,0.01257569,0.0001193273,0.4829384,0.001779429,0.1762743],"genre_scores_gemma":[0.3842933,0.2027069,0.001937483,0.002337252,0.004104264,0.0002420255,0.1995312,0.0006857867,0.2041618],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.07145325,"threshold_uncertainty_score":0.1420747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004692824725146538,"score_gpt":0.2168135527090634,"score_spread":0.2121207279839168,"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."}}