{"id":"W2970509049","doi":"10.18174/sesmo.2020a16226","title":"Eight grand challenges in socio-environmental systems modeling","year":2019,"lang":"en","type":"article","venue":"Socio-Environmental Systems Modeling","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":205,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Vetenskapsrådet; Svenska Forskningsrådet Formas; National Socio-Environmental Synthesis Center; National Science Foundation","keywords":"Underpinning; Management science; Computer science; Bridging (networking); Data science; Knowledge management; Grand Challenges; Adaptation (eye); Scientific modelling; Engineering; Psychology","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":[0.02998665,0.001209396,0.001701585,0.002942967,0.003352877,0.009567534,0.003798291,0.005536603,0.003306952],"category_scores_gemma":[0.02813371,0.0009458375,0.001843224,0.003797977,0.01000162,0.0135156,0.007329118,0.01289055,0.0009442344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00528203,"about_ca_system_score_gemma":0.009370402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007328857,"about_ca_topic_score_gemma":0.008027429,"domain_scores_codex":[0.988022,0.007559131,0.0007695862,0.0009177357,0.002376093,0.0003554221],"domain_scores_gemma":[0.9646376,0.02689435,0.0008696072,0.002854605,0.003644729,0.001099153],"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":[0.00001307978,0.00005175007,0.001030599,0.0004073057,0.0000380927,0.000135064,0.001326146,0.01200956,0.0001753403,0.9340973,0.01006364,0.04065198],"study_design_scores_gemma":[0.000006249762,0.00001910467,0.0002654687,0.0004116333,0.00001155338,0.00009357827,0.001121782,0.01861764,0.0001087902,0.9270778,0.05223053,0.00003576893],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.01099141,0.03417772,0.4858978,0.4394293,0.002075933,0.0002231046,0.0005553793,0.0004443523,0.02620486],"genre_scores_gemma":[0.2049235,0.05274565,0.7178991,0.01000639,0.002994153,0.001070391,0.0006252822,0.0003412025,0.009394285],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.02998665,"threshold_uncertainty_score":0.1585864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1554484110521319,"score_gpt":0.3203116559759072,"score_spread":0.1648632449237754,"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."}}