{"id":"W4398639336","doi":"10.7910/dvn/fmk6sq/ulmjci","title":"645662_1(Colour_1).tif","year":2020,"lang":"fr","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":"Geology; 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":[0.0003028201,0.001039712,0.001014337,0.0002606175,0.0002535641,0.0003348557,0.001629022,0.0009740018,0.04178423],"category_scores_gemma":[0.0004260512,0.001242566,0.0003989108,0.0004252308,0.0002962614,0.0004550509,0.0008428574,0.001889116,0.8520142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004576891,"about_ca_system_score_gemma":0.0002144221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004683319,"about_ca_topic_score_gemma":0.0001064189,"domain_scores_codex":[0.9961833,0.0001621626,0.000785048,0.001111743,0.0006152023,0.001142482],"domain_scores_gemma":[0.9964677,0.0002157517,0.0002226758,0.002218223,0.00007784196,0.0007978263],"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":[0.00004750787,0.00009936539,0.000007545989,0.001343674,0.0004930769,0.0009809567,0.0002589241,0.002936187,0.0001447015,0.0003757034,0.9907089,0.002603452],"study_design_scores_gemma":[0.000878804,0.0001066469,0.00003347836,0.0005373667,0.0006317506,0.00006184094,0.0001118822,0.00510448,0.0001026006,0.00006206716,0.9911378,0.00123127],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008829413,0.00001394225,0.001356052,0.0000745281,0.006536859,0.0004707134,0.988324,0.0006725146,0.002463078],"genre_scores_gemma":[0.0001197098,0.00156379,0.005610412,0.0006770718,0.001792415,0.00005557962,0.9869995,0.0002075616,0.002973934],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.81023,"threshold_uncertainty_score":0.9990024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01996687517047655,"score_gpt":0.2228961773567697,"score_spread":0.2029293021862932,"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."}}