{"id":"W2794604568","doi":"","title":"Rural Broadband Policies in a Cross-National Comparison","year":2016,"lang":"en","type":"article","venue":"","topic":"ICT Impact and Policies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Broadband; Digital divide; Rural area; Internet access; The Internet; Witness; Business; Geography; Economic growth; Political science; Telecommunications; Engineering; Computer science; Economics; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001678645,0.0000833337,0.0001304073,0.001183377,0.001279652,0.002215078,0.0003757504,0.0005299425,0.00613628],"category_scores_gemma":[0.004095553,0.0001049041,0.0002228641,0.002497446,0.0007120459,0.002762107,0.001892286,0.0008559692,0.0003314988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002081453,"about_ca_system_score_gemma":0.001652456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01697356,"about_ca_topic_score_gemma":0.02915599,"domain_scores_codex":[0.9988427,0.000486374,0.000047528,0.00009768523,0.0001479788,0.0003776378],"domain_scores_gemma":[0.9981105,0.0006382542,0.0004284041,0.0001139209,0.0003891862,0.0003195915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0006996301,0.0009538651,0.2811765,0.001006033,0.0002821009,0.002030283,0.06591958,0.005067058,0.001593723,0.4759544,0.0268843,0.1384326],"study_design_scores_gemma":[0.00004113593,0.00040935,0.693472,0.0007299224,0.00008262401,0.000356462,0.1265184,0.0008816194,0.0006347342,0.006709835,0.170117,0.00004703241],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8484327,0.0019156,0.0004448717,0.006084226,0.00009528881,0.0000554352,0.0006771145,0.00001610678,0.1422788],"genre_scores_gemma":[0.9898783,0.002216294,0.0002472684,0.001215629,0.00002658127,0.00005439936,0.0004810333,0.00001286935,0.005867712],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01697356,"threshold_uncertainty_score":0.03374952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01961063223931354,"score_gpt":0.3061611391062204,"score_spread":0.2865505068669069,"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."}}