{"id":"W2562759545","doi":"10.22230/src.2016v7n2/3a253","title":"StructureMorph: Creating Scholarly 3D Models for a Convergent, Digital Publishing Environment","year":2016,"lang":"en","type":"article","venue":"Scholarly and Research Communication","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workflow; Computer science; Premise; Object (grammar); World Wide Web; Data science; Geographic information system; Database; Artificial intelligence; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003998614,0.0007936913,0.0005106474,0.002752903,0.002045531,0.008389425,0.003217385,0.001801681,0.01814802],"category_scores_gemma":[0.00998969,0.0009664394,0.001481008,0.002046424,0.002241223,0.00625728,0.007503195,0.001638326,0.006198325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001411436,"about_ca_system_score_gemma":0.002975269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002195559,"about_ca_topic_score_gemma":0.004772075,"domain_scores_codex":[0.9980007,0.000354705,0.000130153,0.0001765325,0.001264995,0.00007286669],"domain_scores_gemma":[0.9949235,0.001315082,0.0002741735,0.002280209,0.0006232068,0.0005837415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003344326,0.0004946998,0.005199549,0.0008815673,0.00009288577,0.001853078,0.01058569,0.03104735,0.02393168,0.2146353,0.09443697,0.6165068],"study_design_scores_gemma":[0.0002233887,0.0002610668,0.00259695,0.0003860312,0.00008210508,0.001906057,0.002667499,0.1900078,0.03077218,0.06987254,0.70098,0.0002442871],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02287486,0.0002131054,0.8912169,0.001572844,0.0003555476,0.0007282072,0.00110536,0.03953111,0.04240213],"genre_scores_gemma":[0.09579027,0.0004494777,0.8673975,0.0002055158,0.00008355294,0.0004472354,0.002582921,0.006993136,0.02605038],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9916106,"threshold_uncertainty_score":0.06071115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07194828607483404,"score_gpt":0.294785080371618,"score_spread":0.2228367942967839,"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."}}