{"id":"W7104678112","doi":"10.17632/2ndb7297ff.1","title":"Soil Moisture SK4","year":2025,"lang":"","type":"dataset","venue":"Mendeley Data","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reflectometry; Water content; Moisture; Wind speed; Automatic weather station; Weather station; Hydrology (agriculture)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","open_science","research_integrity","insufficient_payload"],"category_scores_codex":[0.004342873,0.003563264,0.003396255,0.001627273,0.001149892,0.001487288,0.03780203,0.002970372,0.01135039],"category_scores_gemma":[0.003555467,0.003877038,0.0004215627,0.003519914,0.0008223326,0.002145872,0.04702308,0.006333708,0.0482991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001286063,"about_ca_system_score_gemma":0.005534716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004696718,"about_ca_topic_score_gemma":0.01297358,"domain_scores_codex":[0.9800902,0.001600691,0.003031257,0.008419066,0.003531063,0.003327701],"domain_scores_gemma":[0.9413869,0.0006289628,0.001856435,0.05454469,0.0005386363,0.001044371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003949958,0.001588912,0.00001524325,0.002174768,0.002571546,0.0007547406,0.00003583161,0.00003643824,0.00007390721,0.0001242818,0.988662,0.003567321],"study_design_scores_gemma":[0.002446954,0.0001489432,0.00002349897,0.001697617,0.00455185,0.0000946029,0.0001601237,0.001165634,0.00005914732,0.0001459485,0.9863691,0.003136601],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000003121914,0.008835918,0.0001092205,0.0008205964,0.005649429,0.001987012,0.9776942,0.0003828673,0.004517646],"genre_scores_gemma":[0.00002043139,0.007186939,0.0007479715,0.001509364,0.002648212,0.0001455434,0.9735554,0.0003511271,0.01383497],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04612563,"threshold_uncertainty_score":0.9995493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0504460871660333,"score_gpt":0.3297139546498192,"score_spread":0.2792678674837858,"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."}}