{"id":"W6944017992","doi":"10.17605/osf.io/arnms","title":"ManyBabies 1: Data Archive","year":2023,"lang":"en","type":"article","venue":"OSF Preprints (OSF Preprints)","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"","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":[0.005392656,0.001961355,0.00284314,0.01247359,0.002368068,0.01061842,0.00481796,0.003233914,0.684165],"category_scores_gemma":[0.06538431,0.001916595,0.002174214,0.01938231,0.001361552,0.004956654,0.005701437,0.003420311,0.5618978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002398032,"about_ca_system_score_gemma":0.009344513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02990584,"about_ca_topic_score_gemma":0.03664364,"domain_scores_codex":[0.9952608,0.000757794,0.0007144205,0.0008473857,0.001576794,0.0008428301],"domain_scores_gemma":[0.9561614,0.01553668,0.002223699,0.01428845,0.009320463,0.002469374],"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":[0.00009533252,0.0000235393,0.0004158193,0.0005324022,0.00004825291,0.0000143056,0.0000667416,0.0001510279,0.00008646021,0.001228749,0.9947118,0.002625537],"study_design_scores_gemma":[0.0002595301,0.00001662388,0.002629352,0.0003925266,0.00005831366,0.00002705021,0.0001680638,0.0003172075,0.0003678177,0.006126742,0.9895717,0.00006511852],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001112773,0.00003183725,0.0003133023,0.0001616764,0.0001214142,0.00003309544,0.9934349,0.002741332,0.003051204],"genre_scores_gemma":[0.002104669,0.0001363417,0.002500559,0.0001791421,0.00008623578,0.0006382224,0.9763952,0.007108274,0.01085128],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.684165,"threshold_uncertainty_score":0.4505002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08104845307569003,"score_gpt":0.2692239878142534,"score_spread":0.1881755347385634,"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."}}