{"id":"W4398492569","doi":"10.7910/dvn/fmk6sq/9slfde","title":"655548_1_S2P(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","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":[0.0003154319,0.001096903,0.001053102,0.0002734507,0.000265946,0.0003492268,0.001711336,0.0009437326,0.03841304],"category_scores_gemma":[0.0004541928,0.001324357,0.0004184549,0.0004494149,0.00032809,0.0004820663,0.0009223725,0.00182056,0.8472188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004878147,"about_ca_system_score_gemma":0.0002360357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004915125,"about_ca_topic_score_gemma":0.0001034013,"domain_scores_codex":[0.995972,0.0001665306,0.0008199296,0.00117109,0.0006534589,0.00121696],"domain_scores_gemma":[0.9962962,0.0002231618,0.0002326711,0.002320851,0.00008053464,0.0008465638],"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":[0.00005038971,0.0001057812,0.000005616726,0.001436557,0.0004901925,0.001005856,0.0003050244,0.003420512,0.0001701757,0.0004147154,0.9897757,0.002819471],"study_design_scores_gemma":[0.0009059865,0.0001310724,0.0000273594,0.0005606097,0.0006078873,0.00007145439,0.0001224632,0.005255439,0.0001027242,0.0000609715,0.9908521,0.001301888],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008797859,0.00001330772,0.001308708,0.00008886912,0.007065743,0.0004910425,0.9880704,0.0007211344,0.002152827],"genre_scores_gemma":[0.000139005,0.001460555,0.005400036,0.0007773385,0.001756706,0.00006016413,0.9870795,0.0002225668,0.003104148],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8088058,"threshold_uncertainty_score":0.9989206,"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."}}