{"id":"W6920908625","doi":"10.6084/m9.figshare.8277248.v1","title":"Jerash Northwest Quarter magnetic data","year":2019,"lang":"en","type":"dataset","venue":"Figshare","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Range (aeronautics); Data set; Mountain range (options)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00008110522,0.0007175902,0.0006198137,0.0002718291,0.0000779166,0.0003340828,0.00529343,0.0006318023,0.8743141],"category_scores_gemma":[0.001112842,0.0007216922,0.0001168426,0.0003364011,0.00001098872,0.0004359351,0.002541338,0.0009674107,0.9302698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000988702,"about_ca_system_score_gemma":0.0003361868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002648859,"about_ca_topic_score_gemma":0.00418981,"domain_scores_codex":[0.9964644,0.0001185297,0.0004547851,0.00144171,0.0008083481,0.0007121745],"domain_scores_gemma":[0.9902181,0.0001389316,0.0004241557,0.00882754,0.0001699864,0.0002213075],"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":[0.000008407223,0.00007360701,0.00000367553,0.001143376,0.00003893788,0.0001370909,0.000004084053,7.736503e-7,8.434922e-7,2.522621e-8,0.9985142,0.00007494098],"study_design_scores_gemma":[0.0003745025,0.00009174857,0.0006785357,0.003553703,0.0001111657,0.00003503934,0.000003935454,0.00002654954,7.700957e-7,6.80814e-7,0.994256,0.0008673589],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[2.7859e-7,0.001350309,1.913905e-9,0.00002233717,0.0002475391,0.0008239343,0.9971491,0.000146231,0.0002602699],"genre_scores_gemma":[0.000002613983,0.000004574114,0.000007929163,0.0002897668,0.0008708115,0.0001871986,0.9974035,0.0002098768,0.001023736],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05595572,"threshold_uncertainty_score":0.9995234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1165204441443262,"score_gpt":0.3210384344133209,"score_spread":0.2045179902689947,"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."}}