{"id":"W4413899267","doi":"10.20944/preprints202509.0084.v1","title":"Optimal Population and Sustainable Growth Under Environmental Constraints","year":2025,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Sustainable Development and Environmental Policy","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"MacEwan University","funders":"","keywords":"Population growth; Population; Sustainable development; Natural resource economics; Economics; Environmental science; Biology; Ecology; Sociology; Demography","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000614493,0.0005774251,0.0004416507,0.0001615152,0.0003855946,0.00005557878,0.0005443905,0.000448923,0.008651678],"category_scores_gemma":[0.00007461911,0.0006484627,0.000135841,0.0001531261,0.0007302861,0.0003277129,0.008340791,0.0007013031,0.001053282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001680534,"about_ca_system_score_gemma":0.00005354103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002318891,"about_ca_topic_score_gemma":0.00001316278,"domain_scores_codex":[0.9965271,0.0001396322,0.000532167,0.001360795,0.0005065178,0.0009337266],"domain_scores_gemma":[0.9988548,0.00005485322,0.000240759,0.0005846085,0.000006294382,0.0002586984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000389657,0.0001514073,0.9905268,0.0001504428,0.00007864495,0.00003752751,0.0006608812,0.00566136,0.0007662945,0.0009483417,0.0002072507,0.0007720606],"study_design_scores_gemma":[0.0004653505,0.0000136335,0.9867343,0.00004340207,0.00006752152,0.00001241295,0.00176413,0.0002121336,0.001821048,0.006629647,0.001587168,0.0006492711],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9626534,0.00006249198,0.0001431733,0.0004024146,0.0001446905,0.0009492518,0.0000342629,0.0001164074,0.03549391],"genre_scores_gemma":[0.9735024,0.0002487686,0.0005485573,0.0004059772,0.00005764085,0.0001552862,0.0001797713,0.00003815809,0.02486342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01084902,"threshold_uncertainty_score":0.9997245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03003021479414823,"score_gpt":0.2762996483382704,"score_spread":0.2462694335441221,"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."}}