{"id":"W4398810728","doi":"10.7910/dvn/u1jec0/p0u9z8","title":"CanRelIncs.tab","year":2020,"lang":"hu","type":"dataset","venue":"Harvard Dataverse","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Replication (statistics); Identity (music); Genealogy; Political science; Internet privacy; Biology; Computer science; History; Art; Virology; Aesthetics","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":[0.000548859,0.00219085,0.001109091,0.002740497,0.001118293,0.002993613,0.002483641,0.001948522,0.289446],"category_scores_gemma":[0.003029885,0.0006093534,0.001099347,0.004486342,0.0005060177,0.001880697,0.002574873,0.001412817,0.3207849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001472316,"about_ca_system_score_gemma":0.001359113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01974091,"about_ca_topic_score_gemma":0.04191003,"domain_scores_codex":[0.9994414,0.00007446394,0.00004140647,0.000157212,0.0001215626,0.0001638536],"domain_scores_gemma":[0.9987202,0.0002286612,0.0001113711,0.000404732,0.0003221277,0.0002130349],"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":[0.00003716518,0.00001044404,0.0002750858,0.0001415211,0.000004459134,0.000004943127,0.000007495093,0.00005866944,0.00002709131,0.0003010444,0.9974588,0.001673375],"study_design_scores_gemma":[0.0001671899,0.00001705679,0.001740864,0.0001186858,0.000007963119,0.00002655404,0.00008729432,0.0003334591,0.0002834428,0.001030128,0.9961703,0.00001690226],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002227591,0.00006523229,0.00004331014,0.0001119988,0.00005429869,0.0000105876,0.9952452,0.000730789,0.003515765],"genre_scores_gemma":[0.0009453851,0.0000812948,0.0001846396,0.0001446396,0.00002508486,0.00004171815,0.9946477,0.0002043357,0.00372523],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.710554,"threshold_uncertainty_score":0.9682932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01684449904306025,"score_gpt":0.2578574978988302,"score_spread":0.24101299885577,"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."}}