{"id":"W2315938711","doi":"10.3167/trans.2016.060107","title":"Target Practice","year":2016,"lang":"en","type":"article","venue":"Transfers","topic":"Geographies of human-animal interactions","field":"Social Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Governmentality; Race (biology); Biopower; Intersection (aeronautics); Sociology; Democracy; Political science; Law and economics; Gender studies; Politics; Law; Geography; Cartography","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":[0.005592977,0.0005603643,0.0004068003,0.00142841,0.01587947,0.0125622,0.002688583,0.005422238,0.08433362],"category_scores_gemma":[0.0128901,0.0003197698,0.0004610298,0.002162977,0.00979923,0.00574821,0.009018093,0.004388278,0.01932557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02861373,"about_ca_system_score_gemma":0.05182801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2927282,"about_ca_topic_score_gemma":0.3262507,"domain_scores_codex":[0.9909321,0.001949454,0.0002534372,0.00149926,0.003316134,0.002049648],"domain_scores_gemma":[0.9924105,0.0009431598,0.0003271147,0.001005991,0.003152844,0.002160393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002145271,0.00005880091,0.001978891,0.00007883447,0.000006597224,0.000292138,0.02486726,0.0002419955,0.0004145465,0.752287,0.1554924,0.06426018],"study_design_scores_gemma":[0.000005292285,0.00001539384,0.0008464769,0.0001833827,0.000002940607,0.0001074139,0.01289543,0.0002592472,0.0001701437,0.02576906,0.9597318,0.00001337109],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.00711845,0.0007188481,0.007941961,0.02877742,0.0007055823,0.0001648513,0.000156888,0.0001414722,0.9542747],"genre_scores_gemma":[0.2598876,0.001716185,0.005739039,0.01581354,0.0002631203,0.0002701335,0.0002662154,0.0002967059,0.7157474],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2927282,"threshold_uncertainty_score":0.5820485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02555463695582674,"score_gpt":0.3358098449900949,"score_spread":0.3102552080342682,"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."}}