{"id":"W4394542883","doi":"10.6084/m9.figshare.19964547","title":"Silicon Valley in the South","year":2022,"lang":"en","type":"dataset","venue":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)","topic":"ICT Impact and Policies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Silicon valley; Geography; Geology; Archaeology; Business","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":[0.0003048483,0.0006467495,0.0006391378,0.002163069,0.0005785241,0.001996859,0.0009134763,0.0007010745,0.02535396],"category_scores_gemma":[0.001376945,0.000320145,0.0005949768,0.006658364,0.0003065717,0.0007922261,0.0013357,0.0009606924,0.01223624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001384297,"about_ca_system_score_gemma":0.002830522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1448207,"about_ca_topic_score_gemma":0.1878928,"domain_scores_codex":[0.9995996,0.00004065717,0.00003629872,0.0001340227,0.00008707344,0.0001022949],"domain_scores_gemma":[0.9993985,0.00009667397,0.0001239112,0.00006933346,0.0002293274,0.00008224009],"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":[0.0001690507,0.00003913824,0.02692402,0.001407376,0.00009475939,0.000186933,0.0001858322,0.0008101164,0.0002088445,0.00311458,0.9529356,0.01392374],"study_design_scores_gemma":[0.0001441237,0.00001201397,0.05749486,0.0006749215,0.00002697189,0.00009207684,0.0007591517,0.0004959999,0.0002890792,0.0008053469,0.9391862,0.00001922914],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004407356,0.0005247137,0.00007083928,0.0004995572,0.00006414265,0.00001483128,0.9876305,0.0001178158,0.006670264],"genre_scores_gemma":[0.009535761,0.0006514661,0.0002462398,0.0002405308,0.0000242016,0.00009587622,0.9853318,0.00005263799,0.003821573],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1448207,"threshold_uncertainty_score":0.2879556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02000152910124549,"score_gpt":0.2401609932398456,"score_spread":0.2201594641386001,"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."}}