{"id":"W2347082338","doi":"10.1002/2015ea000155","title":"Open science in practice: Learning integrated modeling of coupled surface‐subsurface flow processes from scratch","year":2016,"lang":"en","type":"article","venue":"Earth and Space Science","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"University of Southern California; National Science Foundation","keywords":"Workflow; Documentation; Computer science; Earth science; Reuse; Data science; Subsurface flow; Reusability; Earth system science; Software; Systems engineering; Engineering; Geology; Database","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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.01052253,0.0009320106,0.0007522528,0.001093667,0.0007451735,0.00409061,0.002674651,0.001457029,0.004884363],"category_scores_gemma":[0.05142119,0.00061143,0.0009993698,0.001169615,0.001589045,0.005857164,0.0044509,0.002668426,0.0009741528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001336218,"about_ca_system_score_gemma":0.00249586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00155896,"about_ca_topic_score_gemma":0.002042536,"domain_scores_codex":[0.9962181,0.002039916,0.0002555292,0.000656693,0.0007107685,0.0001189053],"domain_scores_gemma":[0.94396,0.0426448,0.002064183,0.006515916,0.003445669,0.001369415],"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":[0.000300339,0.001317902,0.01264186,0.0006244545,0.0001068568,0.0004179421,0.003607361,0.5485278,0.003912099,0.07368845,0.005741147,0.3491137],"study_design_scores_gemma":[0.00007581708,0.0002282458,0.0009721695,0.0001278178,0.00002354384,0.00004963274,0.000401369,0.8659418,0.002862022,0.1190078,0.01027982,0.00002996969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08925761,0.000237198,0.8983107,0.001774722,0.00009313323,0.0002504966,0.0001505093,0.00213246,0.007793332],"genre_scores_gemma":[0.3373483,0.0004061238,0.6581682,0.0001993384,0.00009102776,0.0005762912,0.0004722291,0.0003410064,0.002397395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9973254,"threshold_uncertainty_score":0.0556491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0129152133913784,"score_gpt":0.2538998604393511,"score_spread":0.2409846470479727,"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."}}