{"id":"W6943929402","doi":"10.17632/35wh56287y","title":"IoT-based Dataset of a Tomato Cultivation Under Different Irrigation Regimes","year":2024,"lang":"en","type":"dataset","venue":"Mendeley Data","topic":"Kantian Philosophy and Modern Interpretations","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Irrigation; Crop; Water content; Line (geometry); Degree (music); Air temperature; Moisture; Water use","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001673555,0.0003418148,0.0003837676,0.0002857379,0.0001583022,0.0002428339,0.001058077,0.0001400473,0.002164],"category_scores_gemma":[0.00004867484,0.0002777852,0.00008062658,0.00005025648,0.0002033408,0.0002856147,0.0003881911,0.0003204284,0.000761805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004663945,"about_ca_system_score_gemma":0.0001232267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004409872,"about_ca_topic_score_gemma":0.00188297,"domain_scores_codex":[0.9980764,0.00008553711,0.0006087876,0.0006229815,0.0004073794,0.0001988834],"domain_scores_gemma":[0.9973094,0.0001137285,0.0003413724,0.002084494,0.00009084869,0.00006012227],"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":[0.00002452604,0.0001580958,1.943812e-7,0.0006270537,0.0001988196,0.000004654091,0.0003476421,0.00001425833,0.000009640812,0.01882977,0.9796603,0.0001250301],"study_design_scores_gemma":[0.0002101201,0.00005820911,0.000001475481,0.000550549,0.000440283,0.000001556588,0.0002032917,0.002366842,0.00008002179,0.009121014,0.9866703,0.0002963933],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003434346,0.0002307843,0.0002575837,0.0006269939,0.0008960392,0.0003125286,0.9969129,0.00005280051,0.000676048],"genre_scores_gemma":[0.003200525,0.00002270915,0.00006249703,0.0004424146,0.0005005518,0.00004133007,0.9953964,0.00003183278,0.0003017725],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.009708758,"threshold_uncertainty_score":0.9999675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1022280703892994,"score_gpt":0.3121593624651229,"score_spread":0.2099312920758235,"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."}}