{"id":"W14932847","doi":"10.5751/es-01206-090211","title":"Using the Species–Area Relationship to Set Baseline Targets for Conservation","year":2004,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":167,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bioregion; Biome; Biodiversity; Geography; Vegetation (pathology); Global biodiversity; Habitat; Baseline (sea); Survey data collection; Protected area; Ecology; Environmental resource management; Environmental science; Ecosystem; Statistics; Mathematics; Biology; Fishery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005355143,0.00006788033,0.00008373017,0.000006570442,0.0009144234,0.000007665809,0.00005702756,0.00009973808,0.000145962],"category_scores_gemma":[0.0002322843,0.000053678,0.00004519126,0.00009214435,0.0002612547,0.00006683506,0.00006492143,0.00009281309,0.00003111328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001068247,"about_ca_system_score_gemma":0.00001601146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002641288,"about_ca_topic_score_gemma":0.002428765,"domain_scores_codex":[0.9994837,0.00004338193,0.0001195051,0.0001585535,0.00004180254,0.0001530485],"domain_scores_gemma":[0.9993597,0.0004705707,0.00004577129,0.00007751562,0.00001581764,0.00003060116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000126844,0.0000343191,0.9495886,0.000006017325,0.00003093123,2.666961e-7,0.006106778,0.02010754,0.0003832234,0.009747205,0.0139625,0.00001995843],"study_design_scores_gemma":[0.0003811893,0.00004160997,0.9688996,0.000001942843,0.00002375301,0.000003703057,0.0007576467,0.005479971,0.00001802198,0.01569551,0.008610259,0.00008677693],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9261181,0.00002619635,0.05967398,0.01306744,0.0001580512,0.0003238691,0.00001646575,0.00001753036,0.0005983784],"genre_scores_gemma":[0.9684683,0.000021167,0.02402331,0.006301621,0.00003235655,0.0000425047,0.00002401026,0.000004419564,0.001082324],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04235018,"threshold_uncertainty_score":0.7033098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0600538671383951,"score_gpt":0.2916317724606368,"score_spread":0.2315779053222417,"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."}}