{"id":"W6906859569","doi":"10.17632/4mn2g8cnsf","title":"IIITDMJ_Smoke","year":2023,"lang":"en","type":"dataset","venue":"Mendeley Data","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Satellite image; Satellite; Satellite imagery; Amazon rainforest; Image processing; Moderate-resolution imaging spectroradiometer","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","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.001591384,0.0006966715,0.0007348857,0.0005408686,0.0001598336,0.0002095215,0.009402193,0.0005384787,0.001667599],"category_scores_gemma":[0.001006332,0.000695498,0.00008224955,0.0009220018,0.000121577,0.0004611288,0.00904482,0.001115812,0.6439591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001942312,"about_ca_system_score_gemma":0.0003608151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004028448,"about_ca_topic_score_gemma":0.004584065,"domain_scores_codex":[0.9950595,0.0001918035,0.0006357344,0.00190497,0.001273647,0.0009343484],"domain_scores_gemma":[0.9840893,0.0001400962,0.0003784767,0.01505544,0.00007285966,0.0002638766],"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":[0.00001955662,0.00009084093,0.00000119763,0.0001346913,0.0001599739,0.000327938,0.000002312163,0.00000146605,0.000007240887,0.000005161147,0.9987573,0.0004923429],"study_design_scores_gemma":[0.0003799207,0.00002739853,0.0000162171,0.0001384897,0.00033148,0.00002367658,0.00001465626,0.00007153608,0.000002624029,0.00007196031,0.9981866,0.0007354007],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[6.980213e-7,0.000312794,0.000003225244,0.00008478486,0.001911537,0.0004482859,0.9961603,0.0007699903,0.0003083732],"genre_scores_gemma":[1.641001e-7,0.0006992747,0.0001196425,0.0002049533,0.001094275,0.00006205046,0.9953133,0.0003218268,0.002184542],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6422915,"threshold_uncertainty_score":0.9995496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2282701177399535,"score_gpt":0.3922050436539432,"score_spread":0.1639349259139897,"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."}}