{"id":"W292755374","doi":"","title":"Monitoring of moose-forest interactions in Estonia as a tool for game management decisions.","year":2003,"lang":"en","type":"article","venue":"Alces","topic":"Ecology and biodiversity studies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Forest management; Population; Geography; Estonian; Estimation; Big game; Ecology; Forestry; Environmental protection; Biology; Demography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004070383,0.0002564168,0.000159615,0.0008085045,0.0002647028,0.0003656757,0.0002401455,0.000187704,0.0006811127],"category_scores_gemma":[0.0004526995,0.00008280549,0.0001121326,0.0005447668,0.000124682,0.0003077454,0.0003885688,0.0001278424,0.0001476515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000224738,"about_ca_system_score_gemma":0.0002038522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008703001,"about_ca_topic_score_gemma":0.03268698,"domain_scores_codex":[0.9998239,0.00006863075,0.00001534072,0.00002996409,0.00003990599,0.00002229575],"domain_scores_gemma":[0.9996485,0.00008549564,0.0001371163,0.00002181358,0.0000624076,0.00004458671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002977082,0.00009197099,0.8610306,0.0003873531,0.0001566967,0.001391395,0.001130224,0.001687529,0.01547315,0.0003374245,0.002247599,0.1157684],"study_design_scores_gemma":[0.000003306278,0.0001098078,0.9912454,0.00005049101,0.00003433613,0.0004283991,0.0004572426,0.001039409,0.001139035,0.000105865,0.005378158,0.000008368454],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9775608,0.006408456,0.004266954,0.0001205712,0.00003310233,0.00004529176,0.001566937,0.00005802669,0.009939953],"genre_scores_gemma":[0.9890137,0.001891621,0.004535528,0.00005709883,0.00001375082,0.0000401297,0.001479179,0.000006140904,0.002962827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008703001,"threshold_uncertainty_score":0.01730466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02876722683298263,"score_gpt":0.2805159221099989,"score_spread":0.2517486952770163,"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."}}