{"id":"W4322099298","doi":"10.5194/egusphere-egu23-17529","title":"Socio-metabolic Risks and Tipping Points on Islands","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Global Energy and Sustainability Research","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Sustainability; Vulnerability (computing); Resource (disambiguation); Business; Natural resource economics; Pandemic; Climate change; Distribution (mathematics); Risk analysis (engineering); Environmental resource management; Coronavirus disease 2019 (COVID-19); Economics; Ecology; Computer science; Computer security; Medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007061902,0.0004409447,0.0002829843,0.0009744286,0.003351685,0.005065378,0.000798835,0.001585773,0.008810376],"category_scores_gemma":[0.002063899,0.000187189,0.0003979103,0.0008064344,0.006441742,0.003372318,0.005936059,0.001911093,0.0008315896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002346405,"about_ca_system_score_gemma":0.0009423317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006677143,"about_ca_topic_score_gemma":0.007622689,"domain_scores_codex":[0.9994047,0.0001873135,0.00001670937,0.00007182559,0.0001541929,0.000165405],"domain_scores_gemma":[0.9992862,0.0001634559,0.0001369547,0.00005432262,0.0001403522,0.0002186704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001167715,0.00006009976,0.02220412,0.000335911,0.00005229406,0.002964595,0.03939355,0.006849785,0.00169319,0.8266896,0.01562094,0.0840192],"study_design_scores_gemma":[0.000009366491,0.0001394296,0.03768742,0.0007420558,0.00005398974,0.001487697,0.1064642,0.004441904,0.001092846,0.6552634,0.1925089,0.0001087726],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5074905,0.006930805,0.01468909,0.0344049,0.000611756,0.00008384211,0.000338001,0.0001711004,0.4352801],"genre_scores_gemma":[0.984217,0.002943196,0.001856435,0.0007240993,0.00009645473,0.0000267877,0.000064722,0.00003719548,0.01003415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008810376,"threshold_uncertainty_score":0.0294736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07117273189454967,"score_gpt":0.3470435494679184,"score_spread":0.2758708175733687,"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."}}