{"id":"W3107824081","doi":"10.33568/rbs.2460","title":"Game Damage tendencies by Kaposvár Forestry - from 1998 to 2017","year":2020,"lang":"en","type":"article","venue":"Regional and Business Studies","topic":"Hungarian Social, Economic and Educational Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Forestry; Big game; Quarter (Canadian coin); Agriculture; Hectare; Human settlement; Geography; Environmental protection; Archaeology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001399679,0.0001285512,0.0001410632,0.0009937842,0.00023599,0.0006763487,0.0002140191,0.000144,0.002311431],"category_scores_gemma":[0.0004829575,0.00008748014,0.0001237514,0.0007492411,0.0003448705,0.0003357388,0.0006798471,0.0002792349,0.0002292491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007964263,"about_ca_system_score_gemma":0.0002645653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009468381,"about_ca_topic_score_gemma":0.02179759,"domain_scores_codex":[0.9998247,0.00001495986,0.00001691956,0.00004032343,0.0000519197,0.00005111959],"domain_scores_gemma":[0.9996343,0.00003999442,0.0001893327,0.0000110221,0.00004414647,0.00008122086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001208608,0.00007798491,0.9673428,0.0001018526,0.00006020061,0.0009233049,0.00284748,0.0005911079,0.0009490004,0.0007135078,0.001497693,0.02477412],"study_design_scores_gemma":[0.000001037685,0.00002056192,0.9961343,0.00001492688,0.000005767456,0.0002950837,0.001659433,0.0001094988,0.0001254649,0.00004925125,0.001581479,0.000003282902],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971362,0.0003711975,0.00004382625,0.000038606,0.000005040251,0.000004346817,0.0004506636,0.000004020977,0.00194606],"genre_scores_gemma":[0.9987094,0.0002020928,0.00002798206,0.000009549432,0.000003091319,0.000002293114,0.000373651,0.00000137512,0.0006706241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009468381,"threshold_uncertainty_score":0.01882654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1347362093791528,"score_gpt":0.3386556510952858,"score_spread":0.203919441716133,"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."}}