{"id":"W2097515863","doi":"10.22230/cjc.2013v38n3a2736","title":"Earth Observation and Signal Territories: Studying U.S. Broadcast Infrastructure through Historical Network Maps, Google Earth, and Fieldwork","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Communication","topic":"Radio, Podcasts, and Digital Media","field":"Social Sciences","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Materialism; Phenomenology (philosophy); Earth system science; Representation (politics); Earth observation; Earth (classical element); Geography; Media studies; Sociology; Geology; Engineering; Oceanography; Epistemology; Political science; Astronomy; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003034093,0.00008698294,0.0001671924,0.00005630535,0.0006324203,0.0003631661,0.0002561283,0.0001119387,0.00007448425],"category_scores_gemma":[0.0002321486,0.00008491232,0.00003054017,0.0001711701,0.0002233466,0.0011891,0.00002114488,0.0002827712,0.000002056781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001662408,"about_ca_system_score_gemma":0.0004463824,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0381851,"about_ca_topic_score_gemma":0.07271794,"domain_scores_codex":[0.9990357,0.0001920976,0.0002844901,0.00008110246,0.000182572,0.0002240772],"domain_scores_gemma":[0.9988093,0.0002331491,0.0002061909,0.0001711628,0.0001958211,0.0003843173],"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":[0.00003255832,0.00003555208,0.3624468,0.00003502418,0.00009705871,0.00002117,0.0974489,0.0002688362,0.00006207499,0.02523358,0.09328566,0.4210328],"study_design_scores_gemma":[0.0003146973,0.000120941,0.1899973,0.0001376515,0.00002234354,0.00003108912,0.00682439,0.00005517674,0.000005523199,0.0189845,0.7833304,0.0001760837],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9552246,0.01828411,0.0003129411,0.0109778,0.001248408,0.0003624526,0.00000620752,0.00001811403,0.01356534],"genre_scores_gemma":[0.9944618,0.0008629915,0.003315351,0.0003046411,0.0007320434,0.000003350354,0.000005908042,0.000007576695,0.0003062855],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6900447,"threshold_uncertainty_score":0.9682197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03114213189490502,"score_gpt":0.2437486994454506,"score_spread":0.2126065675505455,"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."}}