{"id":"W2910255777","doi":"10.1080/08941920.2018.1511023","title":"Public Brainpower: Civil Society and Natural Resource Management","year":2019,"lang":"en","type":"article","venue":"Society & Natural Resources","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Natural Resources; University of Calgary","funders":"","keywords":"Natural resource management; Natural resource; Civil society; Natural (archaeology); Resource (disambiguation); Resource management (computing); Political science; Environmental ethics; Environmental resource management; Environmental planning; Natural resource economics; Geography; Economics; Politics; Computer science; Archaeology; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024354,0.0003943693,0.0002528604,0.001154609,0.003015959,0.007595284,0.0005576975,0.006006348,0.03612287],"category_scores_gemma":[0.005472058,0.0001410465,0.0001683815,0.001433034,0.01129024,0.005398035,0.002971687,0.003123074,0.001375689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005062733,"about_ca_system_score_gemma":0.009296073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007752081,"about_ca_topic_score_gemma":0.01536173,"domain_scores_codex":[0.9989238,0.0005703249,0.0000192861,0.00006407541,0.0001472938,0.0002751557],"domain_scores_gemma":[0.995523,0.002377804,0.0004096673,0.00008891027,0.000383297,0.001217368],"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":[0.00002939495,0.0001424854,0.002302684,0.00008121501,0.000009105383,0.0001741797,0.001388713,0.0003862208,0.00006587387,0.8934932,0.0527912,0.04913578],"study_design_scores_gemma":[0.00002558575,0.00004620264,0.005468514,0.0003503712,0.00001468977,0.0001935631,0.007754467,0.0005794897,0.0001357575,0.7701328,0.2152787,0.00001986033],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02537825,0.02608494,0.002794279,0.5790096,0.002920457,0.00002293991,0.0000838355,0.00003549866,0.3636703],"genre_scores_gemma":[0.8829932,0.01978045,0.0006477861,0.03695137,0.0062369,0.00005460249,0.00005348034,0.0000289727,0.0532533],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03612287,"threshold_uncertainty_score":0.120843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006751459817951591,"score_gpt":0.2191953533307008,"score_spread":0.2124438935127493,"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."}}