{"id":"W2059255771","doi":"10.1111/j.1523-1739.2007.00699.x","title":"Long‐Term Ecosystem Dynamics in the Serengeti: Lessons for Conservation","year":2007,"lang":"en","type":"article","venue":"Conservation Biology","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":201,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of British Columbia","funders":"National Research Council Canada","keywords":"Ecology; Ecosystem; Wildebeest; Predation; Geography; Abiotic component; Wildlife; Population; Disturbance (geology); Vegetation (pathology); Biology; National park","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.001863205,0.0001383094,0.0001596577,0.00006825374,0.0002120317,0.00001889484,0.0003019454,0.0002486439,0.0001546598],"category_scores_gemma":[0.0002511729,0.0001133289,0.00004962253,0.0003346617,0.0001673247,0.0001666599,0.00004952014,0.0001461648,0.00008847525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000288064,"about_ca_system_score_gemma":0.0000336029,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002766304,"about_ca_topic_score_gemma":0.06506441,"domain_scores_codex":[0.9986597,0.0001934389,0.0004242285,0.0003073587,0.00008351511,0.000331805],"domain_scores_gemma":[0.9985002,0.000975597,0.0001947546,0.0002573635,0.00003699033,0.00003504374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006395352,0.00005146931,0.9637256,0.000009686338,0.000006743247,0.000002090046,0.0001644286,0.00001211165,0.0002444508,0.03052427,0.002452214,0.002743004],"study_design_scores_gemma":[0.0005527865,0.00008720645,0.9836476,0.000008240841,0.00001124676,0.00001307593,0.0002198376,0.004769163,0.00005817533,0.00334799,0.007149317,0.0001353885],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9414376,0.00001808885,0.02104288,0.03495783,0.0003171258,0.0007046935,0.00002735591,0.00003983069,0.001454585],"genre_scores_gemma":[0.9883035,0.00001009671,0.0005455015,0.01036635,0.0000614196,0.0001375413,0.0003597466,0.000009667194,0.0002061308],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06478778,"threshold_uncertainty_score":0.9519957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02860834822148631,"score_gpt":0.2816541225431549,"score_spread":0.2530457743216686,"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."}}