{"id":"W4394478236","doi":"10.6084/m9.figshare.12294743","title":"Chinese mystery snail random forest model R code and databases","year":2020,"lang":"en","type":"dataset","venue":"Figshare","topic":"Morphological variations and asymmetry","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Code (set theory); Database; Random forest; Computer science; Programming language; Artificial intelligence","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":[0.001867895,0.001577702,0.0007759331,0.001795022,0.0006783789,0.001024962,0.002994158,0.001130024,0.03203412],"category_scores_gemma":[0.006676141,0.0007281632,0.001220832,0.00231106,0.0005383334,0.0007410545,0.001028662,0.001404766,0.03308991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001278532,"about_ca_system_score_gemma":0.002462188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03304767,"about_ca_topic_score_gemma":0.06227953,"domain_scores_codex":[0.9994364,0.0001105012,0.00005877232,0.0002121911,0.0001124327,0.00006962359],"domain_scores_gemma":[0.9985058,0.0005694327,0.00009153038,0.0003482645,0.0003839161,0.0001011458],"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":[0.0002691755,0.00009527381,0.007053494,0.0006801024,0.0001203136,0.0001147546,0.00007241237,0.009166357,0.0004718805,0.001682902,0.9674723,0.01280105],"study_design_scores_gemma":[0.001277581,0.000151129,0.02161832,0.0004317728,0.0002225491,0.0003680016,0.0001379874,0.0610717,0.002761294,0.01049719,0.9013178,0.0001446924],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003525315,0.0001234316,0.003445481,0.0001429919,0.00006572246,0.0001659767,0.9845978,0.006005875,0.001927385],"genre_scores_gemma":[0.004685933,0.000061875,0.00577276,0.00007672187,0.000009308457,0.0005730855,0.9873417,0.0005234665,0.0009551694],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03304767,"threshold_uncertainty_score":0.1071649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1331015662637713,"score_gpt":0.3422690996139104,"score_spread":0.209167533350139,"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."}}