{"id":"W6948154976","doi":"10.48550/arxiv.1712.02281","title":"SAND: An automated VLBI imaging and analysing pipeline - I. Stripping component trajectories","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Very-long-baseline interferometry; Pipeline (software); Deconvolution; Component (thermodynamics); Data reduction; Reduction (mathematics); Interferometry; Data processing","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":[0.0008226591,0.001366161,0.0008840418,0.002233183,0.0008979278,0.001677891,0.001819061,0.0008196516,0.01161933],"category_scores_gemma":[0.001691742,0.001076056,0.001052339,0.00138252,0.000412259,0.0009715997,0.001229384,0.001171044,0.01200816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008690965,"about_ca_system_score_gemma":0.0021322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007333997,"about_ca_topic_score_gemma":0.007493734,"domain_scores_codex":[0.999386,0.00003805901,0.00004901609,0.0001960982,0.0002337901,0.0000971995],"domain_scores_gemma":[0.9992952,0.0001201662,0.00006808066,0.0002254241,0.0002345688,0.00005642685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000810054,0.0002892459,0.01386284,0.0005748674,0.0002262553,0.0003858636,0.0005371172,0.02239163,0.3733615,0.007329165,0.07974894,0.5004826],"study_design_scores_gemma":[0.0001798704,0.0001985219,0.02911884,0.00007032098,0.0001194244,0.0006555509,0.0002091112,0.4782386,0.3083138,0.01240444,0.1701327,0.0003588158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01704539,0.000107162,0.8535823,0.0001251139,0.00007831759,0.0003295568,0.009527383,0.115917,0.003287764],"genre_scores_gemma":[0.05013059,0.0001361507,0.9169379,0.0001549028,0.00004046141,0.0006611226,0.01941069,0.007381066,0.005146936],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01161933,"threshold_uncertainty_score":0.03887051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04963908419268494,"score_gpt":0.2200213981735287,"score_spread":0.1703823139808438,"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."}}