{"id":"W2061299452","doi":"10.1353/tech.2002.0132","title":"Telecom Nation: Telecommunications, Computers, and Governments in Canada (review)","year":2002,"lang":"en","type":"article","venue":"Technology and Culture","topic":"History of Computing Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Telecommunications; Scholarship; Politics; State (computer science); Work (physics); Political science; Engineering; Law; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007262537,0.0001073296,0.0001644183,0.0001038403,0.0001215981,0.00001254667,0.0008249739,0.0001169738,0.000006940164],"category_scores_gemma":[0.00005158262,0.00009980895,0.000008768119,0.0005384319,0.0001099551,0.0001102742,0.0004318748,0.0003190822,0.000004639508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001768963,"about_ca_system_score_gemma":0.00003683264,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003310304,"about_ca_topic_score_gemma":0.0534491,"domain_scores_codex":[0.9993036,0.00002473716,0.000159344,0.0002426427,0.0001087032,0.0001609743],"domain_scores_gemma":[0.9993777,0.00002740795,0.0000705062,0.0004759264,0.00002434431,0.00002406133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[7.856395e-7,0.00007302132,0.01678241,0.000123975,0.00002719942,0.00004512228,0.0004335866,0.000005364538,0.00008904926,0.1096704,0.2891337,0.5836154],"study_design_scores_gemma":[0.0006395775,0.0001000495,0.006153595,0.0005385248,0.000009046729,0.00034909,0.0002628334,0.009951941,0.0002947459,0.01100169,0.9701627,0.0005362366],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.09268391,0.5980893,0.01390866,0.2832664,0.0005634048,0.0009916649,0.000008317616,0.002424988,0.008063339],"genre_scores_gemma":[0.8820368,0.0227219,0.09255325,0.002197959,0.0000085533,0.00002918109,0.000001861132,0.000006803226,0.0004437063],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7893529,"threshold_uncertainty_score":0.963823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01055392421222505,"score_gpt":0.1941939433203432,"score_spread":0.1836400191081182,"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."}}