{"id":"W4398537536","doi":"10.7910/dvn/fmk6sq/vhp6x0","title":"634214_2(Colour_1).tif","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Dyeing and Modifying Textile Fibers","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001124283,0.0004793361,0.0004765426,0.000160307,0.00007843752,0.0001301226,0.0008779417,0.000400662,0.008617538],"category_scores_gemma":[0.0001176508,0.0005310068,0.0001596504,0.0001844693,0.00007984118,0.0001668752,0.0002933564,0.0008015443,0.408841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001225724,"about_ca_system_score_gemma":0.00006347104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006947981,"about_ca_topic_score_gemma":0.0000308724,"domain_scores_codex":[0.9983603,0.00003528225,0.0003304213,0.0004691191,0.0003276753,0.0004771761],"domain_scores_gemma":[0.9982919,0.00005773285,0.00006898056,0.001264875,0.00002584802,0.0002907009],"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":[0.000009614127,0.00001596698,3.168411e-7,0.0003999697,0.0001377927,0.0002178473,0.00002911544,0.0007616943,0.00002436154,0.000008438467,0.9979268,0.0004680353],"study_design_scores_gemma":[0.0002924667,0.00002874275,0.000003402258,0.0001125201,0.0001516265,0.00001470528,0.00001641404,0.0009687014,0.00002795293,0.00001174489,0.997816,0.0005557123],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000089139,0.000002614588,0.0001566985,0.000005633357,0.002183593,0.0001956004,0.995855,0.0007850704,0.0008068626],"genre_scores_gemma":[0.00002959474,0.0005225152,0.0004603083,0.0003400616,0.0005610153,0.00003223829,0.9977128,0.00008508311,0.0002563972],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4002234,"threshold_uncertainty_score":0.9997141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589096941692385,"score_gpt":0.2124488036771322,"score_spread":0.1965578342602084,"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."}}