{"id":"W4398593441","doi":"10.7910/dvn/28117/y4cqnx","title":"dyadicAggregations.2005.to.2013.tgz","year":2015,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001164933,0.0005831502,0.0007030928,0.0009578213,0.0001930627,0.0008511298,0.008178229,0.0003435022,0.007049167],"category_scores_gemma":[0.0007349611,0.000570566,0.0001808851,0.00119522,0.0001081289,0.001742308,0.004142555,0.0005892889,0.5771465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002892212,"about_ca_system_score_gemma":0.0007778199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001394855,"about_ca_topic_score_gemma":0.001428038,"domain_scores_codex":[0.9953567,0.0002215265,0.0006755405,0.00149077,0.001439519,0.0008159286],"domain_scores_gemma":[0.9901409,0.000120037,0.0004340738,0.008028606,0.0002992984,0.0009770909],"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":[0.000006385969,0.00008916408,0.000002291658,0.00002756013,0.0001153991,0.000161389,0.0000257812,0.00003803474,0.00000210286,0.0002011154,0.9982499,0.001080811],"study_design_scores_gemma":[0.0003177468,0.00004971514,0.00001238186,0.0000792295,0.0001659611,0.00003834233,0.00001017115,0.0007322974,0.00000742069,0.0001360737,0.9977882,0.0006624444],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[9.167037e-7,0.000003937602,0.02170761,0.0002133031,0.001186464,0.0003719246,0.9760512,0.000214073,0.0002506457],"genre_scores_gemma":[8.322132e-7,0.0001688049,0.02007629,0.002090369,0.0003934151,0.00006144322,0.9759511,0.00002747819,0.001230268],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5700973,"threshold_uncertainty_score":0.9996746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02079495711066796,"score_gpt":0.2599442021539244,"score_spread":0.2391492450432565,"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."}}