{"id":"W4394509096","doi":"10.6084/m9.figshare.8970704","title":"Client fish traits underlying variation in service quality in a marine cleaning mutualism","year":2019,"lang":"en","type":"dataset","venue":"Figshare","topic":"Marine Bivalve and Aquaculture Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mutualism (biology); Marine fish; Fishery; Fish <Actinopterygii>; Ecology; Biology","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":[0.001546011,0.0008521138,0.0007967261,0.002343355,0.0006887873,0.001323961,0.001733896,0.0009846429,0.1325505],"category_scores_gemma":[0.008210205,0.0006454638,0.001008702,0.003645764,0.0002559415,0.0009443369,0.001926685,0.0010817,0.06040559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001363963,"about_ca_system_score_gemma":0.001536003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04002311,"about_ca_topic_score_gemma":0.08420415,"domain_scores_codex":[0.9992148,0.0001414466,0.0001412118,0.0002365331,0.0001579835,0.0001080594],"domain_scores_gemma":[0.9955979,0.001275083,0.0006827634,0.00109401,0.001073512,0.0002767428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008726927,0.00001578535,0.007827044,0.0006169732,0.00005873617,0.00002070808,0.00007988537,0.0002438315,0.0001599132,0.000475962,0.9877671,0.002646843],"study_design_scores_gemma":[0.0004508828,0.00003481819,0.09557929,0.0006815169,0.0001091491,0.00009066679,0.0003456395,0.0005528121,0.0006203057,0.002015084,0.8994433,0.00007642536],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002546718,0.00001048876,0.00007141306,0.00003905556,0.00000671962,0.00001504576,0.9989551,0.00009882994,0.0005486087],"genre_scores_gemma":[0.001902649,0.00002193626,0.0007683971,0.00006286651,0.000006504227,0.000346019,0.994978,0.0001465407,0.001767059],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1325505,"threshold_uncertainty_score":0.4434257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08554486227918849,"score_gpt":0.3226599858320511,"score_spread":0.2371151235528626,"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."}}