{"id":"W4285040128","doi":"10.5281/zenodo.6049135","title":"Backgrounder – 2011 Canadian Research Data Summit","year":2011,"lang":"en","type":"report","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Dementia Research Alliance","funders":"","keywords":"Summit; Political science; Geography; Cartography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.04256622,0.002063853,0.001487746,0.01320856,0.01795775,0.02095028,0.005711315,0.005316654,0.04626738],"category_scores_gemma":[0.06572092,0.001501393,0.001942935,0.01651295,0.003070285,0.004442439,0.008816354,0.007386228,0.02563987],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.1518852,"about_ca_system_score_gemma":0.4295723,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9857762,"about_ca_topic_score_gemma":0.9872673,"domain_scores_codex":[0.9047765,0.00424905,0.003067167,0.003749114,0.07264927,0.01150888],"domain_scores_gemma":[0.8698291,0.005659427,0.002052147,0.005645319,0.09950353,0.01731053],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002897058,0.00001424214,0.0006529694,0.00009890278,0.000008166214,0.00002509424,0.0001429444,0.00008158862,0.00007982587,0.00345114,0.9895262,0.005889975],"study_design_scores_gemma":[0.000009360855,0.000006144949,0.004724903,0.0001375246,0.000008195458,0.00000882529,0.0003309976,0.00007883138,0.0002051334,0.000266341,0.994187,0.00003670103],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.00552029,0.009856615,0.002908528,0.1752916,0.02068402,0.002473948,0.4230992,0.003239163,0.3569266],"genre_scores_gemma":[0.03564304,0.01137256,0.01117553,0.04204009,0.002661718,0.0027993,0.4028987,0.002031193,0.4893777],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9942887,"threshold_uncertainty_score":0.983693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.465457096500911,"score_gpt":0.3858394453288433,"score_spread":0.0796176511720677,"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."}}