{"id":"W3182161332","doi":"10.1080/08941920.2021.1936318","title":"Salish Sea Survey: Geographic Literacy Enhancing Natural Resource Management","year":2021,"lang":"en","type":"article","venue":"Society & Natural Resources","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Karen C. Drayer Wildlife Health Center","keywords":"Outreach; Geography; Natural resource; Environmental resource management; Natural resource management; Literacy; Ecosystem management; Resource management (computing); Resource (disambiguation); Geographic information system; Ecosystem; Ecology; Political science; Biology; Cartography","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":[0.0008249977,0.0001915735,0.0001541276,0.001777281,0.000672431,0.0004931117,0.0005395295,0.0003085583,0.005439864],"category_scores_gemma":[0.002943336,0.0001557392,0.0001656501,0.002689131,0.0002665475,0.0006076142,0.001273803,0.0004880101,0.001211536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001479562,"about_ca_system_score_gemma":0.002511602,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2464037,"about_ca_topic_score_gemma":0.380105,"domain_scores_codex":[0.9994823,0.0001349814,0.00009417441,0.00004479212,0.0001732463,0.00007056917],"domain_scores_gemma":[0.9979162,0.0002120755,0.0004948127,0.0001116422,0.0008607042,0.0004046859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008074824,0.0003337555,0.876897,0.0002250888,0.00003386434,0.0001327654,0.001935857,0.0001758544,0.0005787569,0.0004222662,0.07653996,0.04264408],"study_design_scores_gemma":[0.00002080343,0.00005305385,0.9749494,0.00004346322,0.00000831093,0.00005193034,0.001603567,0.0001331854,0.0001592878,0.00007145245,0.02289679,0.000008857474],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7842813,0.0004017919,0.001196013,0.002868274,0.00009145779,0.003035078,0.1580544,0.0002577845,0.0498139],"genre_scores_gemma":[0.8251513,0.00107614,0.01009309,0.001357545,0.0001160422,0.006216471,0.1347906,0.00005538883,0.02114339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7535963,"threshold_uncertainty_score":0.4899389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01050999156489275,"score_gpt":0.2791553455977782,"score_spread":0.2686453540328854,"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."}}