{"id":"W6943796369","doi":"10.17605/osf.io/uyzxw","title":"ManyBabies","year":2017,"lang":"en","type":"other","venue":"Open Science Framework","topic":"Spreadsheets and End-User Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Work (physics); Product (mathematics); Identification (biology); Process (computing)","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":[],"consensus_categories":[],"category_scores_codex":[0.002444959,0.001374998,0.001152557,0.002922641,0.00235908,0.007407781,0.002655257,0.00188545,0.5255802],"category_scores_gemma":[0.00758424,0.0006778332,0.001054095,0.002438103,0.0009147798,0.005790249,0.006291294,0.003003843,0.4477662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001656189,"about_ca_system_score_gemma":0.00258629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006254819,"about_ca_topic_score_gemma":0.007100311,"domain_scores_codex":[0.9982138,0.0003209753,0.00004728367,0.0003071221,0.0007791586,0.0003317411],"domain_scores_gemma":[0.9951811,0.0007042093,0.0001485893,0.001159244,0.001426182,0.001380587],"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":[0.0001746069,0.0001278262,0.0002604485,0.0001338553,0.00001058165,0.00005008066,0.0001255445,0.0002380867,0.0008776992,0.0501214,0.8424386,0.1054413],"study_design_scores_gemma":[0.00002898458,0.00001433913,0.0002404864,0.00005816926,0.000003768701,0.00004256923,0.00006269182,0.0009163208,0.0007015893,0.0103685,0.9875497,0.00001276872],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002738404,0.001468534,0.05792232,0.004636042,0.001792875,0.0002157367,0.01600363,0.1108788,0.8043438],"genre_scores_gemma":[0.01772977,0.001142254,0.03489726,0.001218435,0.0005103,0.0002413656,0.03597248,0.06487744,0.8434108],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5255802,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03673277723497394,"score_gpt":0.3464349421633605,"score_spread":0.3097021649283866,"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."}}