{"id":"W4200578112","doi":"10.5539/ijef.v14n1p58","title":"Broadband Market Sizing in Brazil","year":2021,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"ICT Impact and Policies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Broadband; Metropolitan area; Census; Logistic regression; Econometrics; Market penetration; Business; Geography; Telecommunications; Economics; Statistics; Computer science; Marketing; Demography; Population; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0007501263,0.0003194697,0.0002903989,0.001673903,0.0002822363,0.00165346,0.0004255897,0.0002881654,0.005018611],"category_scores_gemma":[0.003834896,0.0002330027,0.0006503431,0.001615461,0.0002599999,0.001445199,0.0005528674,0.0003353947,0.0004419214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001906906,"about_ca_system_score_gemma":0.001493101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06396302,"about_ca_topic_score_gemma":0.05414331,"domain_scores_codex":[0.999683,0.00006493829,0.00002119341,0.00007103796,0.0001012947,0.00005846467],"domain_scores_gemma":[0.9989226,0.0004143489,0.0003085136,0.00004624248,0.0002398433,0.00006839138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001080062,0.0001348019,0.6460862,0.0004257151,0.0002215858,0.00116984,0.0007831995,0.1075493,0.002545752,0.1435851,0.01125065,0.08613988],"study_design_scores_gemma":[0.00003890201,0.0001361039,0.4303394,0.000291887,0.0001492283,0.0007537876,0.002612898,0.4672804,0.001926265,0.04375242,0.05265548,0.00006326608],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9124983,0.001498513,0.01764948,0.001882783,0.00002681524,0.0001392579,0.01065784,0.000229831,0.05541714],"genre_scores_gemma":[0.9939963,0.0004766588,0.001877846,0.00002971462,0.000009244403,0.00003084464,0.0019806,0.00001455723,0.001584268],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06396302,"threshold_uncertainty_score":0.1271814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007622953429945978,"score_gpt":0.2244408793653155,"score_spread":0.2168179259353696,"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."}}