{"id":"W6906398528","doi":"10.17605/osf.io/mxe7n","title":"Kaolin and IOT Characterisation","year":2022,"lang":"en","type":"article","venue":"OSF Preprints (OSF Preprints)","topic":"Soil and Unsaturated Flow","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Constant (computer programming); Internet of Things; Soil water; Test (biology); Stress (linguistics)","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":[0.0002457968,0.0003806689,0.0002144064,0.002403896,0.0005011339,0.001235078,0.0004380266,0.0004651026,0.005154324],"category_scores_gemma":[0.00043524,0.0001382336,0.0002282983,0.001329164,0.0004360591,0.0007219613,0.0005133971,0.0003230177,0.002448323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005635615,"about_ca_system_score_gemma":0.0004891656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003579374,"about_ca_topic_score_gemma":0.007751175,"domain_scores_codex":[0.9995584,0.00001942939,0.00003086698,0.00009164574,0.0002171183,0.00008250119],"domain_scores_gemma":[0.999691,0.00003389684,0.00005106457,0.00003297291,0.0001602069,0.00003098706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000831564,0.0001338191,0.03093852,0.0006565602,0.0000371065,0.0008900193,0.001025694,0.004955363,0.8746669,0.004955357,0.00341117,0.07749795],"study_design_scores_gemma":[0.00003512515,0.0005580572,0.05648624,0.000104129,0.00008757942,0.001537925,0.001675802,0.01282578,0.791092,0.003246929,0.1322133,0.0001370079],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9051258,0.0006944888,0.02571945,0.0001815134,0.00009240345,0.0002893393,0.004188749,0.0005823643,0.06312589],"genre_scores_gemma":[0.9769032,0.000442059,0.004353151,0.00009091316,0.00002063611,0.0001110222,0.002059001,0.00013927,0.01588076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005154324,"threshold_uncertainty_score":0.01724291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009062330845659678,"score_gpt":0.2057086688626356,"score_spread":0.1966463380169759,"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."}}