{"id":"W3034737931","doi":"10.1111/cag.12632","title":"Being genealogical in digital geographies","year":2020,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Foregrounding; Scholarship; Narrative; Discipline; TRACE (psycholinguistics); Futures contract; Sociology; Temporalities; Object (grammar); Genealogy; Media studies; Geography; History; Social science; Political science; Linguistics; Art; Literature; Law","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":[0.003245541,0.0002818701,0.000225995,0.003118683,0.01062646,0.01018139,0.0009067429,0.001280856,0.006623966],"category_scores_gemma":[0.00943801,0.000221572,0.0001537533,0.004595787,0.0590711,0.009253051,0.00543123,0.002248524,0.0004906266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01018651,"about_ca_system_score_gemma":0.007995355,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0881855,"about_ca_topic_score_gemma":0.1292679,"domain_scores_codex":[0.9977464,0.001160947,0.00006471292,0.0003398914,0.0004110014,0.0002769176],"domain_scores_gemma":[0.9946724,0.002825616,0.0004866799,0.0009503646,0.0006542492,0.0004107525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000005379485,0.000002955334,0.0007060685,0.00001676599,0.000001440829,0.00005630922,0.0451947,0.00008969333,0.00006860727,0.9472367,0.00122297,0.005398329],"study_design_scores_gemma":[0.000007663843,0.00001555817,0.002156192,0.0002197867,0.00001141607,0.0003323786,0.0769172,0.000270255,0.0003596547,0.2903032,0.6293778,0.00002887746],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1488538,0.005584222,0.04006365,0.03140146,0.0009983664,0.0001052988,0.0003368972,0.0002250669,0.7724313],"genre_scores_gemma":[0.9748249,0.001613342,0.004157661,0.0008074,0.0001149692,0.00004415133,0.00007852323,0.00009432831,0.01826475],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9118145,"threshold_uncertainty_score":0.1753444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01593330605219803,"score_gpt":0.2174006088701637,"score_spread":0.2014673028179657,"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."}}