{"id":"W4255415603","doi":"10.1163/2210-7975_hrd-4943-2014012","title":"Governing Natural Resources for Africa�s Development - Canada and Africa�s Natural Resources: Key Features 2013","year":2016,"lang":"en","type":"dataset","venue":"Human Rights Documents online","topic":"Transboundary Water Resource Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Natural resource; Natural (archaeology); Key (lock); Geography; Political science; Computer science; Archaeology; Computer security","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":[0.001367701,0.002108143,0.001419691,0.007931024,0.001237807,0.003410124,0.002453691,0.001930747,0.03790133],"category_scores_gemma":[0.008654858,0.000964181,0.001241028,0.01797473,0.0005864936,0.00170464,0.00199726,0.002116368,0.02882117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008637418,"about_ca_system_score_gemma":0.01812724,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6434962,"about_ca_topic_score_gemma":0.7326719,"domain_scores_codex":[0.9985756,0.0001193232,0.0001708673,0.0002015541,0.0005769814,0.0003557871],"domain_scores_gemma":[0.9952126,0.0008825922,0.0004809633,0.000580955,0.002171789,0.0006711309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00003475394,0.00001431282,0.001344732,0.0003009509,0.00001533641,0.00001136667,0.00001943744,0.0002824934,0.00003497667,0.0005700982,0.9954849,0.001886517],"study_design_scores_gemma":[0.0001331868,0.000005907113,0.01412576,0.0005271544,0.00002954528,0.00002909505,0.0001519616,0.0005225348,0.0003125985,0.0009615506,0.9831641,0.00003645211],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008363022,0.00003726503,0.00001592779,0.00004768015,0.000009620607,0.000004481466,0.9991575,0.00005180708,0.0005920153],"genre_scores_gemma":[0.0004367033,0.00009383265,0.0001078254,0.00002879062,0.000003879801,0.00003596014,0.9982712,0.00003045173,0.0009913549],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3565038,"threshold_uncertainty_score":0.7172067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01523637775883689,"score_gpt":0.2730563507488729,"score_spread":0.257819972990036,"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."}}