{"id":"W4398909015","doi":"10.7910/dvn/s3hacj/rphtyg","title":"Codebook_aggregate_dataset.pdf","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Codebook; Aggregate (composite); Computer science; Artificial intelligence; Materials 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":[0.001844133,0.003764818,0.002284246,0.005894297,0.001129717,0.003945693,0.004891072,0.003333015,0.1822535],"category_scores_gemma":[0.0111908,0.001008933,0.001935681,0.008546363,0.0009215161,0.003020125,0.003931243,0.002317814,0.2270477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00246312,"about_ca_system_score_gemma":0.003357914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03608606,"about_ca_topic_score_gemma":0.05892949,"domain_scores_codex":[0.9984236,0.0003129256,0.0001671405,0.000456326,0.0003394298,0.0003006017],"domain_scores_gemma":[0.9964858,0.0009993564,0.0002726477,0.0009005494,0.0009140452,0.000427513],"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":[0.00002797223,0.000008787576,0.0001351107,0.0004221352,0.00001841627,0.000006486544,0.000008713505,0.0001310003,0.00003353781,0.0002246713,0.9978026,0.001180584],"study_design_scores_gemma":[0.000416454,0.00004138151,0.002143967,0.0005490322,0.00005309677,0.00006917548,0.00009488688,0.0009380977,0.0003768793,0.002765937,0.9924924,0.00005877815],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005794309,0.0001026939,0.00006246873,0.0001055864,0.00004156396,0.0000117787,0.9983705,0.0006843083,0.0005631413],"genre_scores_gemma":[0.0002946205,0.00008231733,0.0002220905,0.00008773781,0.00001474888,0.00006883802,0.9982976,0.0001494795,0.0007826902],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8177465,"threshold_uncertainty_score":0.6096988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02201042883844537,"score_gpt":0.2491321980095712,"score_spread":0.2271217691711259,"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."}}