{"id":"W4393839403","doi":"10.5281/zenodo.6401266","title":"Assessing ambitious nature conservation strategies in a below 2-degree and food-secure world – supplementary spatial data","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Degree (music); Food security; Geography; Environmental resource management; Computer science; Environmental science","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":[0.00283203,0.0007066584,0.0004216278,0.003296457,0.0004286765,0.001314767,0.001461346,0.0005998207,0.02517939],"category_scores_gemma":[0.01213691,0.0002606917,0.0008785211,0.005777233,0.0004295611,0.001336132,0.00151422,0.000614553,0.002830634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002485221,"about_ca_system_score_gemma":0.002775612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1670612,"about_ca_topic_score_gemma":0.2436229,"domain_scores_codex":[0.9985159,0.0004523504,0.000112204,0.0002126625,0.0005524734,0.0001544347],"domain_scores_gemma":[0.9925112,0.002299433,0.0008862636,0.0009462647,0.002925542,0.0004313498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000646023,0.0005668632,0.3483108,0.001776391,0.0008237591,0.0007561459,0.001636891,0.3461394,0.002535801,0.02640635,0.1653122,0.1050894],"study_design_scores_gemma":[0.000430146,0.0004083488,0.4449605,0.001008865,0.0004010335,0.0002829427,0.009620399,0.2125007,0.00474367,0.02472475,0.300581,0.0003376615],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.2448799,0.0003988415,0.02298486,0.001232672,0.0001136925,0.001040207,0.674183,0.001579184,0.05358769],"genre_scores_gemma":[0.6363314,0.0003219977,0.06561826,0.0001432967,0.00002451077,0.001998271,0.2892871,0.0002958257,0.005979327],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1670612,"threshold_uncertainty_score":0.3321776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05649404928182355,"score_gpt":0.2802409339930619,"score_spread":0.2237468847112384,"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."}}