{"id":"W2595764972","doi":"10.1080/01426397.2017.1290791","title":"Re-conceptualising political landscapes after the material turn: a typology of material events","year":2017,"lang":"en","type":"article","venue":"Landscape Research","topic":"Geographies of human-animal interactions","field":"Social Sciences","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Materiality (auditing); Typology; Politics; Collective action; Sociology; Epistemology; Perspective (graphical); Aesthetics; Corporate governance; Environmental ethics; Political science; Anthropology; Philosophy; Law; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001640004,0.0001034238,0.0002053782,0.0001669229,0.001671017,0.0004160767,0.0009968831,0.0001536966,0.007819542],"category_scores_gemma":[0.0008524834,0.00007262621,0.0001010871,0.0001127255,0.001257413,0.0002725932,0.0003884071,0.0003039066,0.0001123193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003943162,"about_ca_system_score_gemma":0.0001119581,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.009831107,"about_ca_topic_score_gemma":0.03541676,"domain_scores_codex":[0.9972535,0.0007318054,0.0002429205,0.0002407687,0.0007052124,0.0008257795],"domain_scores_gemma":[0.9985079,0.0003977002,0.0001019559,0.0005550006,0.000290388,0.0001470553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005995044,0.0008346671,0.4910042,0.0001894183,0.0004770918,0.0001713719,0.056089,0.000002063255,0.007368052,0.3860094,0.0510319,0.0008278019],"study_design_scores_gemma":[0.001968388,0.0009799342,0.641925,0.0003157978,0.0001112832,0.00003044944,0.1946878,0.00003394562,0.005375956,0.04375916,0.1100158,0.0007964653],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9206936,0.00004621497,1.944421e-7,0.005623524,0.0008601727,0.0002284209,0.00007154393,0.00002415571,0.07245216],"genre_scores_gemma":[0.9976946,0.00004475084,0.00003134726,0.00003893554,0.001299729,0.00005144465,0.000008323547,0.00001425102,0.000816628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3422503,"threshold_uncertainty_score":0.9996287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0875398085717644,"score_gpt":0.4438165676521039,"score_spread":0.3562767590803395,"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."}}