{"id":"W3043284752","doi":"","title":"Where do we go from here?: Science Communications Post-IPY Lessons Learned from Canada (Invited)","year":2010,"lang":"en","type":"article","venue":"AGUFM","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009395404,0.0005356292,0.0005645604,0.001582569,0.02293354,0.01562859,0.002157151,0.01137968,0.03213478],"category_scores_gemma":[0.02020398,0.0006401498,0.0004999333,0.003140853,0.00491399,0.00450039,0.005651494,0.01389345,0.004207759],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07050157,"about_ca_system_score_gemma":0.2411935,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.954645,"about_ca_topic_score_gemma":0.9811347,"domain_scores_codex":[0.9931421,0.0005053993,0.0001860831,0.0004692787,0.002912945,0.002784309],"domain_scores_gemma":[0.9745737,0.003200867,0.000493669,0.0003107277,0.01145319,0.009967833],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004922277,0.00002038423,0.001599845,0.0001226435,0.000006921905,0.00032502,0.004963853,0.00005800158,0.0002353446,0.003844215,0.9684128,0.02036181],"study_design_scores_gemma":[0.00001449701,0.00001479391,0.005720223,0.000189366,0.000009852685,0.00006154677,0.01832988,0.00004716749,0.000224049,0.0007765192,0.9745765,0.00003569783],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.004046401,0.005152317,0.0001928613,0.9581642,0.009289554,0.00003754766,0.0004024307,0.00007701326,0.02263767],"genre_scores_gemma":[0.1333902,0.01790604,0.001355769,0.383649,0.004598184,0.0001294754,0.0007626048,0.000409687,0.4577991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9906046,"threshold_uncertainty_score":0.5115271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1212615414530212,"score_gpt":0.3753898844066169,"score_spread":0.2541283429535957,"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."}}