{"id":"W3018492874","doi":"10.5281/zenodo.896613","title":"Galaxy Mergers Moulding The Cgm","year":2017,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0001880938,0.0004506329,0.0002563929,0.0002367939,0.0005464983,0.0009897801,0.0005309813,0.0007982202,0.002393222],"category_scores_gemma":[0.001244754,0.0002362583,0.0006438749,0.0002458317,0.0007855671,0.0007500438,0.000904792,0.000598559,0.0002629433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008356535,"about_ca_system_score_gemma":0.0003932472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007596758,"about_ca_topic_score_gemma":0.005143772,"domain_scores_codex":[0.9998876,0.00002287232,0.000004212004,0.00003013893,0.00002597445,0.00002919756],"domain_scores_gemma":[0.9997776,0.00006724957,0.00004694504,0.00003529826,0.00001745207,0.00005548538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004910166,0.0002380784,0.1684663,0.0003032503,0.0003861973,0.002442735,0.001713689,0.6756746,0.07425126,0.04648629,0.005244498,0.02430214],"study_design_scores_gemma":[0.0002393424,0.0006067315,0.1658671,0.00007819903,0.0002320043,0.001285088,0.001047293,0.7663223,0.01718914,0.02444862,0.02256774,0.0001164439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855951,0.000310163,0.004618767,0.0004027477,0.00004040262,0.00002476537,0.0003079237,0.0003308814,0.008369152],"genre_scores_gemma":[0.9974179,0.0001272549,0.001190219,0.00009379573,0.0000119287,0.000009018177,0.0001513205,0.00005091921,0.0009476353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007596758,"threshold_uncertainty_score":0.01510507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02962739492680387,"score_gpt":0.2304991041117154,"score_spread":0.2008717091849115,"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."}}