{"id":"W1985018337","doi":"10.2481/dsj.4.21","title":"Rescuing and recovering lost or endangered data","year":2005,"lang":"en","type":"article","venue":"Data Science Journal","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dominion Astrophysical Observatory; Herzberg Institute of Astrophysics","funders":"","keywords":"Scope (computer science); Computer science; Transparency (behavior); Open data; Metadata; Usability; Reuse; Data science; Implementation; World Wide Web; Data curation; Open science; Engineering; Software engineering; Computer security","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":["scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001840256,0.00009339402,0.0001000224,0.0001196775,0.0004126667,0.002539361,0.007528788,0.00001803821,0.00002196971],"category_scores_gemma":[0.0002795089,0.00006570332,0.00000888563,0.000621687,0.0002886826,0.02111246,0.00657994,0.000193836,0.00004820587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004215307,"about_ca_system_score_gemma":0.0003369909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007468132,"about_ca_topic_score_gemma":0.00006239803,"domain_scores_codex":[0.998228,0.00001222256,0.0002209034,0.0005769674,0.0005829153,0.0003789991],"domain_scores_gemma":[0.9976349,0.00004189458,0.0001026348,0.001900333,0.0000643173,0.0002559084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005843674,0.00002481808,0.0003033376,0.000002959497,0.000004526695,0.00005407867,0.0002292279,0.00001282551,0.0006239468,0.003042965,0.01335666,0.9823388],"study_design_scores_gemma":[0.0005524473,0.0001297205,0.005094686,0.0001471533,0.00001208146,0.005457228,0.0001905631,0.3062987,0.001317035,0.002794568,0.6775013,0.0005045437],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2837887,0.002513954,0.611541,0.02397785,0.006986304,0.0005015326,0.001778075,0.0004200705,0.06849254],"genre_scores_gemma":[0.535657,0.0007955978,0.4597428,0.001546102,0.001247856,5.037006e-7,0.00007665662,0.00001658468,0.0009168095],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9818343,"threshold_uncertainty_score":0.9984961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1006452456693089,"score_gpt":0.3114684138730922,"score_spread":0.2108231682037833,"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."}}