{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.001128234,0.0003287104,0.0004165056,0.00035035,0.0009494658,0.007178038,0.03240414,0.0002828757,0.0005742763],"category_scores_gemma":[0.0004880055,0.000278704,0.00007260504,0.0006871513,0.0007395564,0.001184708,0.01045109,0.0004798908,0.0009285925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006790313,"about_ca_system_score_gemma":0.0005467876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006893525,"about_ca_topic_score_gemma":0.00005550388,"domain_scores_codex":[0.996865,0.00003243878,0.0001806509,0.001343088,0.0008248836,0.0007539392],"domain_scores_gemma":[0.9944201,0.00008006267,0.0004200751,0.004759273,0.00006778363,0.0002526663],"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":[8.037417e-7,0.00002733988,0.0002017104,0.00001411496,0.00001268605,0.00003611886,0.0002384223,0.000005555674,0.00001164077,0.2072588,0.6550553,0.1371375],"study_design_scores_gemma":[0.00007359096,0.00002489869,0.000340544,0.0009605133,0.000004315925,0.00001066946,0.000009726564,0.001268777,0.00005445975,0.01390394,0.9828911,0.0004574326],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000005398568,0.0003477703,0.1549293,0.000649102,0.003564326,0.0003241276,0.000003035183,0.0003073961,0.8398696],"genre_scores_gemma":[0.00146134,0.00007525704,0.3899186,0.0006209586,0.0006201657,0.00002283673,0.000001006948,0.0001326634,0.6071472],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3278359,"threshold_uncertainty_score":0.9999665,"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."}}