{"id":"W4404414929","doi":"10.1093/ismeco/ycae142","title":"Putative past, present, and future spatial distributions of deep-sea coral and sponge microbiomes revealed by predictive models","year":2024,"lang":"en","type":"article","venue":"ISME Communications","topic":"Coral and Marine Ecosystems Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada","funders":"German Academic Exchange Service; Fisheries and Oceans Canada; Deutscher Akademischer Austauschdienst","keywords":"Microbiome; Identification (biology); Biodiversity; Coral; Temporal scales; Host (biology); Ecology; Trait; Taxon; Environmental resource management; Biology; Geography; Environmental science; Computer science; Bioinformatics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00008668494,0.0001023697,0.0001366544,0.00002531208,0.0002434481,0.00002985298,0.0002130231,0.00003818082,0.00004581809],"category_scores_gemma":[0.000005231603,0.00008789575,0.00003004342,0.0001679009,0.0004566975,0.000205644,0.001005173,0.0001182572,0.000007646688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005122975,"about_ca_system_score_gemma":0.00000685241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008325306,"about_ca_topic_score_gemma":0.0004152522,"domain_scores_codex":[0.9993618,0.00008456311,0.0001733688,0.0001826432,0.00007845652,0.0001191658],"domain_scores_gemma":[0.9993973,0.000137139,0.00005054879,0.0003403352,0.00001986728,0.00005481488],"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":[0.0002050018,0.001470882,0.2885273,0.0008552886,0.001129149,0.00001449765,0.0331176,0.00015598,0.01452568,0.01906765,0.3127157,0.3282153],"study_design_scores_gemma":[0.0007988579,0.0003227409,0.5406435,0.0001525365,0.000324808,0.00005666579,0.002353302,0.1372458,0.000281795,0.01723154,0.3000023,0.0005861828],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6804521,0.07612526,0.07036051,0.1094737,0.0007686326,0.004084024,0.02192794,0.0005515533,0.03625624],"genre_scores_gemma":[0.9967452,0.001775062,0.0006738209,0.00001243137,0.00005510303,0.00007148711,0.0002092655,0.000007116408,0.0004505655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3276291,"threshold_uncertainty_score":0.3584285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01205470760135124,"score_gpt":0.2431368349110095,"score_spread":0.2310821273096583,"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."}}