{"id":"W2123404750","doi":"10.1023/b:land.0000030666.55372.ae","title":"Using normative scenarios in landscape ecology","year":2004,"lang":"en","type":"article","venue":"Landscape Ecology","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":189,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Landscape ecology; Normative; Futures contract; Environmental resource management; Ecology; Landscape assessment; Landscape epidemiology; Environmental planning; Geography; Landscape design; Environmental science; Political science; Business; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001925832,0.0001503182,0.0002191666,0.000136432,0.00009611937,0.00001602406,0.0002429989,0.0001445911,0.01167604],"category_scores_gemma":[0.00003340157,0.0001378326,0.0000422192,0.0003311071,0.0001132715,0.0001848424,0.000253145,0.0001726693,0.004610851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001660926,"about_ca_system_score_gemma":0.00002324241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005012649,"about_ca_topic_score_gemma":0.01496435,"domain_scores_codex":[0.998831,0.00006742097,0.0002304006,0.0002684715,0.00009863427,0.0005041281],"domain_scores_gemma":[0.999603,0.00005383027,0.00008204736,0.0001836303,0.000003930003,0.0000735861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002694115,0.0001154317,0.9437176,0.000005602221,0.0000112341,0.00006657034,0.0009712906,0.04924642,0.0000897489,0.0008110132,0.004704902,0.0002332561],"study_design_scores_gemma":[0.002658765,0.0002544796,0.9697058,0.000008330375,0.00002112413,0.00004389419,0.0001587914,0.01180825,0.00004750443,0.002690789,0.01225805,0.0003442726],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9223652,0.0000140306,0.00002088208,0.0007742377,0.0002823356,0.0002174868,0.000002157122,0.00003647422,0.07628721],"genre_scores_gemma":[0.9970333,0.00001868621,0.0007269583,0.00110403,0.00008246539,0.00001993164,0.00001334648,0.0000132987,0.0009880125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0752992,"threshold_uncertainty_score":0.9961642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01265474755284023,"score_gpt":0.246341060173578,"score_spread":0.2336863126207378,"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."}}