{"id":"W7037679022","doi":"","title":"Entangled Territorialities: Negotiating Indigenous Lands in Australia and Canada","year":2023,"lang":"en","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Indigenous; Negotiation; Work (physics); Government (linguistics); State (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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002536235,0.0001885165,0.00044577,0.00110295,0.01299692,0.006279691,0.001920766,0.001742941,0.004821918],"category_scores_gemma":[0.01131332,0.0004130107,0.0002872238,0.002198692,0.01137465,0.002763096,0.005697276,0.001690984,0.0001530505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02764901,"about_ca_system_score_gemma":0.03982585,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9699975,"about_ca_topic_score_gemma":0.9899676,"domain_scores_codex":[0.9979352,0.0006482184,0.00004711772,0.0002343756,0.000369045,0.0007661068],"domain_scores_gemma":[0.9960498,0.002100031,0.0003121277,0.0002678348,0.0006438132,0.0006263142],"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":[0.0001441515,0.00009158967,0.09922903,0.0001805685,0.0001650787,0.001858374,0.3269711,0.0183793,0.0008316496,0.4798505,0.006790909,0.06550764],"study_design_scores_gemma":[0.00002478559,0.00004051575,0.1078271,0.000342548,0.0001398234,0.0003651231,0.6619067,0.02439483,0.0004991011,0.1281353,0.07618432,0.0001398247],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9082239,0.0005956666,0.007139115,0.00378212,0.00001612014,0.0000656862,0.0001138939,0.0000223697,0.08004116],"genre_scores_gemma":[0.9952351,0.0001144876,0.001252038,0.00006175737,0.000001758478,0.00001151989,0.00001650697,0.000009119938,0.003297771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03000253,"threshold_uncertainty_score":0.2006086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02767567601827648,"score_gpt":0.233976058003994,"score_spread":0.2063003819857175,"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."}}