{"id":"W4392514258","doi":"10.21203/rs.3.rs-3945941/v1","title":"Determination of the performance of Antarctic Ozone Hole Area using Artificial Neural Network","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Calcutta","keywords":"Artificial neural network; Environmental science; Computer science; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.001786367,0.0001285225,0.00019746,0.00006535911,0.0002247993,0.00003924485,0.000420715,0.0001386218,0.00008092844],"category_scores_gemma":[0.0001626099,0.0000978898,0.0001214607,0.0005246829,0.0004713062,0.00005603913,0.002455726,0.001028252,0.00001388026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002760728,"about_ca_system_score_gemma":0.0000616841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007569066,"about_ca_topic_score_gemma":0.00003921723,"domain_scores_codex":[0.9975631,0.0003131499,0.0003610085,0.0003187949,0.001062762,0.0003812353],"domain_scores_gemma":[0.9990966,0.0001742936,0.0001642103,0.0004541727,0.00005986316,0.00005088959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009093562,0.0001430368,0.2470036,0.003296668,0.00002483548,0.000008765315,0.002608929,0.6675462,0.0107438,0.00007054839,0.0001431578,0.0683195],"study_design_scores_gemma":[0.00003773549,0.0001414212,0.03853787,0.002017453,0.00002391618,0.000003611245,0.0002335211,0.9458513,0.01045122,0.002520232,0.000033631,0.0001481157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984998,0.000126982,0.00008996803,0.00009536374,0.0004996316,0.0003425513,0.00001853198,0.00001563217,0.0003116127],"genre_scores_gemma":[0.9989467,0.00001718798,0.0005979736,0.000002104787,0.0002963376,0.00001366009,0.000004885197,0.00001889992,0.0001021994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2783051,"threshold_uncertainty_score":0.4467302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1284562644495885,"score_gpt":0.3779883789086714,"score_spread":0.2495321144590829,"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."}}