{"id":"W4398845976","doi":"10.7910/dvn/qvtakg/ziu4e1","title":"wave 1+2.tab","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Material Properties and Failure Mechanisms","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008241016,0.003756765,0.002287725,0.004467018,0.0009454848,0.004229159,0.004004105,0.003354424,0.2347414],"category_scores_gemma":[0.005034463,0.001137212,0.001907174,0.008066862,0.0005844407,0.0024132,0.002611399,0.002141871,0.2989588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001506985,"about_ca_system_score_gemma":0.001902332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0154656,"about_ca_topic_score_gemma":0.02276688,"domain_scores_codex":[0.9992265,0.0001003937,0.00007723101,0.0002833473,0.0001551597,0.0001574611],"domain_scores_gemma":[0.9983428,0.0004624485,0.0001594792,0.000477783,0.0003304822,0.0002270825],"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":[0.00003881839,0.00001326915,0.0002188234,0.0006353754,0.00002235731,0.00001063598,0.000009537491,0.000208034,0.00007399556,0.0003815377,0.9972684,0.001119223],"study_design_scores_gemma":[0.0003557686,0.00002668744,0.00147527,0.0003599286,0.00003825707,0.00004753637,0.00004608578,0.0005924082,0.0003787098,0.002326947,0.9943212,0.00003117077],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004648594,0.00006830325,0.00004279713,0.00004557317,0.0000208279,0.0000057739,0.9985092,0.0005975924,0.0006632706],"genre_scores_gemma":[0.0002829983,0.00008550355,0.000175375,0.00007005616,0.000009697821,0.00004354883,0.9984699,0.0001804856,0.0006824614],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7652586,"threshold_uncertainty_score":0.7852884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02477101201241548,"score_gpt":0.2136502398984029,"score_spread":0.1888792278859874,"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."}}