{"id":"W2920833540","doi":"10.1017/s1551929519000026","title":"Management, Analysis, and Simulation of Micrographs with Cloud Computing","year":2019,"lang":"en","type":"article","venue":"Microscopy Today","topic":"Big Data Technologies and Applications","field":"Decision Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Automotive Fuel Cell Cooperation (Canada)","funders":"","keywords":"Cloud computing; Micrograph; Computer science; Materials science; Computer graphics (images); Operating system; Composite material","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":[],"consensus_categories":[],"category_scores_codex":[0.0004490101,0.00008365964,0.0002154134,0.0003430206,0.00007420983,0.00009802247,0.0003944628,0.00004791792,0.00006747532],"category_scores_gemma":[0.0000188044,0.00005823327,0.00005129788,0.001951668,0.0001177884,0.00008917051,0.0002031007,0.0000594388,0.00003964708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005860595,"about_ca_system_score_gemma":0.000004523352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002655747,"about_ca_topic_score_gemma":0.00001820888,"domain_scores_codex":[0.9989443,0.00002269428,0.000292249,0.0003609192,0.0002453965,0.0001344326],"domain_scores_gemma":[0.9988305,0.0002062426,0.0002080595,0.0006481076,0.00008244615,0.00002467603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004655344,0.0001081664,0.8618858,0.00002755629,0.000375522,0.000001725049,0.0002170944,0.01079729,0.03725883,0.00400776,0.001261073,0.08401258],"study_design_scores_gemma":[0.002021062,0.0004547865,0.6862413,0.0001133051,0.0007804696,0.000005641704,0.004121982,0.07645918,0.08527841,0.009825923,0.1338471,0.0008508835],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.911364,0.0001123561,0.08740448,0.0001262758,0.00003098053,0.0001931357,0.00003248873,0.00003605365,0.0007002252],"genre_scores_gemma":[0.9780585,0.00002080728,0.02157841,0.00004516273,0.000005481293,0.000001790143,0.00001585947,0.000004380895,0.0002695991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1756446,"threshold_uncertainty_score":0.2374684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04500624072573308,"score_gpt":0.3587634838371366,"score_spread":0.3137572431114036,"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."}}