{"id":"W2395690085","doi":"10.5281/zenodo.3781776","title":"Data Rescue in Canada, a Case Study","year":2010,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Computer security; Business","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"],"consensus_categories":[],"category_scores_codex":[0.002653808,0.0006515895,0.0004361421,0.002383338,0.0229976,0.004980882,0.002764038,0.005311527,0.003535265],"category_scores_gemma":[0.009932292,0.0004413821,0.0006164109,0.00926631,0.00532717,0.001556913,0.003015546,0.002597714,0.0004803519],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06624492,"about_ca_system_score_gemma":0.08017927,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9764591,"about_ca_topic_score_gemma":0.9889365,"domain_scores_codex":[0.995756,0.000812561,0.0002080448,0.0003679568,0.001473822,0.001381617],"domain_scores_gemma":[0.9922312,0.002052257,0.0004436596,0.0003370701,0.002737119,0.002198725],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0006287025,0.001147655,0.122677,0.00160548,0.0002004213,0.229104,0.2661664,0.01660782,0.003678298,0.06045728,0.1550693,0.1426576],"study_design_scores_gemma":[0.00008153063,0.0001413118,0.05843504,0.0005943527,0.00007388065,0.01658453,0.4790646,0.005905735,0.001467129,0.004091209,0.4333632,0.0001975335],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8231956,0.005913896,0.007429267,0.04907396,0.0003893242,0.001139319,0.004826363,0.0003388686,0.1076934],"genre_scores_gemma":[0.9500437,0.004293902,0.009042486,0.003603494,0.00006831542,0.000199639,0.001316767,0.0001345353,0.03129721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9973462,"threshold_uncertainty_score":0.4806427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2674311170619187,"score_gpt":0.3860331813118557,"score_spread":0.118602064249937,"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."}}