{"id":"W6893874844","doi":"10.5281/zenodo.5508996","title":"Cothurnia sinuosa","year":2021,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Marine Invertebrate Physiology and Ecology","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Epibiont; Algae; Variety (cybernetics); Abundance (ecology); Biodiversity","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00007547746,0.0005096979,0.0001998106,0.001585399,0.001262725,0.0003566805,0.0002559588,0.000228659,0.008804844],"category_scores_gemma":[0.0002119023,0.000162316,0.0001414692,0.001113579,0.0004158506,0.0004140032,0.000734082,0.0002859955,0.000894943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004530294,"about_ca_system_score_gemma":0.000479715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02673326,"about_ca_topic_score_gemma":0.07643335,"domain_scores_codex":[0.9999287,0.000004057271,0.000008149726,0.00002724623,0.00001823219,0.00001366427],"domain_scores_gemma":[0.9998724,0.00001121345,0.00004445835,0.00001289681,0.00003126014,0.00002775899],"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":[0.000882988,0.0001750825,0.2998734,0.001618517,0.00013144,0.004400709,0.003325105,0.0009033351,0.2022206,0.002508387,0.007370303,0.4765902],"study_design_scores_gemma":[0.00004547231,0.0003036283,0.9389236,0.000235783,0.00007180819,0.002674266,0.002007324,0.0003603756,0.005265193,0.0003764479,0.04970472,0.00003131382],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9290459,0.002714756,0.0007316687,0.0001121056,0.0001609699,0.0001442828,0.001388254,0.000110541,0.06559162],"genre_scores_gemma":[0.9902789,0.0009505973,0.0006847908,0.0001321747,0.00003443283,0.00004488953,0.0009129642,0.000008075027,0.006953083],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02673326,"threshold_uncertainty_score":0.0531553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02571259095161393,"score_gpt":0.2074110009802805,"score_spread":0.1816984100286665,"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."}}