{"id":"W4394296674","doi":"10.6084/m9.figshare.1080737.v12","title":"Legislative correlates of the size and number of protected areas in Canadian jurisdictions","year":2015,"lang":"en","type":"dataset","venue":"Figshare","topic":"Environmental Conservation and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Legislature; Environmental science; Geography; Political science; Law","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005205286,0.0001082635,0.0001270707,0.00002591683,0.00003671209,0.0000061226,0.0002092968,0.0001030506,0.1550441],"category_scores_gemma":[0.0003483227,0.00008677534,0.00002686353,0.0001876295,0.00005253541,0.00006093154,0.0002801063,0.0001649068,0.0004675951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002006766,"about_ca_system_score_gemma":0.00005592437,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1887896,"about_ca_topic_score_gemma":0.4847499,"domain_scores_codex":[0.9992986,0.00004798521,0.0001724715,0.000157727,0.0001945458,0.000128666],"domain_scores_gemma":[0.9994534,0.00004655992,0.0001605004,0.0002505771,0.000006860295,0.00008215544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000192046,0.00001875195,0.005145552,0.00003798966,0.000007027518,0.000001551949,0.00007933541,0.0000276107,0.000001914583,6.852499e-7,0.994646,0.00003163707],"study_design_scores_gemma":[0.0001050824,0.0000088206,0.1595111,0.0003029808,0.000008893374,0.000001338787,0.00001967295,0.00001436145,0.000008215551,0.00001994146,0.8399263,0.00007333854],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005255269,0.0000168953,8.72774e-9,0.0001194743,0.00002427086,0.0005100941,0.9939415,0.000002773344,0.004859444],"genre_scores_gemma":[0.005220584,0.00000651467,0.00001219058,0.0001633688,0.000004495169,0.0001190157,0.9937786,0.000006236291,0.0006889887],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2959603,"threshold_uncertainty_score":0.8457283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01813472966239739,"score_gpt":0.2356034943674338,"score_spread":0.2174687647050365,"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."}}