{"id":"W4411614381","doi":"10.1111/csp2.70087","title":"Protected area targets: Spatially evaluating progress and prioritizing areas to reach 30 × 30 in Canada","year":2025,"lang":"en","type":"article","venue":"Conservation Science and Practice","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"World Wildlife Fund Canada","funders":"","keywords":"Regional science; Geography; Environmental planning; Environmental resource management; Computer science; Environmental science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002654813,0.00009747302,0.0001187414,0.00006919268,0.0003683128,0.0002004178,0.0001808178,0.00002837176,0.00007744633],"category_scores_gemma":[0.002349725,0.00008421913,0.000004609485,0.0009774305,0.00006307671,0.001180378,0.0002001062,0.00009639591,0.00001057964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003425997,"about_ca_system_score_gemma":0.0008546009,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5203736,"about_ca_topic_score_gemma":0.6178129,"domain_scores_codex":[0.9984602,0.0001275371,0.0002463677,0.0004000462,0.0005133203,0.0002525666],"domain_scores_gemma":[0.9990793,0.0004035971,0.0001261124,0.0001635649,0.0001221467,0.0001052562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009024234,0.00003588535,0.9363359,0.00008742479,0.000007212395,0.00002084997,0.001519949,0.0001539557,0.0112029,0.00006943739,0.0004264102,0.05004982],"study_design_scores_gemma":[0.0004934577,0.00007206611,0.935048,0.0002529488,0.00002305636,0.00002243359,0.001945412,0.03989505,0.0009999998,0.0001754936,0.0208138,0.0002582444],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852242,0.0001469253,0.00007759656,0.01071691,0.00008699657,0.0005934417,0.000002286635,0.00001449724,0.003137152],"genre_scores_gemma":[0.9938402,0.00002172208,0.002358707,0.003674722,0.000009571976,0.00006680022,0.000001478881,0.000003275847,0.00002359041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09743935,"threshold_uncertainty_score":0.4828203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03178810199655097,"score_gpt":0.3072073541686052,"score_spread":0.2754192521720543,"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."}}