{"id":"W4411949200","doi":"10.21203/rs.3.rs-6972835/v1","title":"Safeguarding global terrestrial vertebrate species from future sea-level rise","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; Environment and Climate Change Canada; Sun Yat-sen University; National Natural Science Foundation of China","keywords":"Safeguarding; Vertebrate; Sea level rise; Environmental resource management; Business; Geography; Fishery; Ecology; Biology; Environmental science; Climate change","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001292286,0.0002500532,0.0003217441,0.000823629,0.0005768242,0.001629248,0.0002694044,0.001189227,0.0116866],"category_scores_gemma":[0.007506893,0.0001682053,0.0001800194,0.001112406,0.0006457539,0.001450985,0.0009137061,0.0006051178,0.002133496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004036245,"about_ca_system_score_gemma":0.001282257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004092889,"about_ca_topic_score_gemma":0.004865161,"domain_scores_codex":[0.999671,0.0001121093,0.000013824,0.00005532343,0.0001145278,0.00003329473],"domain_scores_gemma":[0.9985889,0.0007062599,0.0001269539,0.000232623,0.0002585275,0.00008672645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002517259,0.00007814564,0.02938398,0.000722141,0.0001065461,0.000513775,0.001651294,0.02509688,0.01693886,0.3095688,0.0792682,0.5364197],"study_design_scores_gemma":[0.00004393307,0.00006785176,0.02507479,0.0003179749,0.00007725693,0.0004748318,0.003485231,0.04838264,0.01522386,0.6889433,0.2178673,0.00004102545],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3473491,0.007504948,0.3160889,0.0581799,0.003892679,0.00014451,0.007635743,0.001468045,0.2577361],"genre_scores_gemma":[0.8395388,0.004906733,0.08157533,0.001527095,0.001052308,0.00008615428,0.002836489,0.0006209578,0.06785595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0116866,"threshold_uncertainty_score":0.03909552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07282002498448069,"score_gpt":0.3329307253068451,"score_spread":0.2601107003223644,"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."}}