{"id":"W4224281218","doi":"10.12681/eadd/51337","title":"Ανάπτυξη συστήματος προσομοίωσης υδατικών πόρων αγροτικών λεκανών απορροής υπό συνθήκες κλιματικής μεταβλητότητας και αλλαγής","year":2022,"lang":"el","type":"dissertation","venue":"","topic":"Process Optimization and Integration","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001641338,0.00080858,0.0006200525,0.001368948,0.002976678,0.007064143,0.001304297,0.002455008,0.08505207],"category_scores_gemma":[0.006821855,0.0005568964,0.0005859963,0.001180397,0.003853159,0.006408073,0.003297579,0.003120422,0.0319667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002822404,"about_ca_system_score_gemma":0.003638062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005167312,"about_ca_topic_score_gemma":0.004545406,"domain_scores_codex":[0.9975496,0.0004178546,0.00009476366,0.0005335112,0.00108589,0.0003183949],"domain_scores_gemma":[0.996944,0.000792241,0.0002337124,0.0004366852,0.001178436,0.0004147817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004101182,0.0002267776,0.003370254,0.001433522,0.00007274099,0.001337113,0.01809994,0.001444245,0.02316265,0.6120292,0.09423536,0.2441781],"study_design_scores_gemma":[0.00003654217,0.00007383728,0.00340758,0.0004685172,0.00004167277,0.0006127263,0.007644046,0.0008973714,0.006058116,0.1035999,0.8770871,0.00007251451],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03343158,0.006734895,0.07939228,0.02265991,0.002409888,0.000229662,0.0009898223,0.001328459,0.8528236],"genre_scores_gemma":[0.4086057,0.01021525,0.05293651,0.005439002,0.00120526,0.0004504783,0.001293877,0.001463099,0.5183907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08505207,"threshold_uncertainty_score":0.2845275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005314922716463884,"score_gpt":0.238501208410923,"score_spread":0.2331862856944591,"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."}}