{"id":"W7081968606","doi":"10.36487/acg_repo/2515_67","title":"Monitoring success: remote sensing and artificial intelligence for tracking success of individual seedlings at a revegetation trial in northern Canada","year":2025,"lang":"en","type":"article","venue":"Mine closure","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Revegetation; Multispectral image; Land reclamation; Vegetation (pathology); Random forest; Satellite imagery; Seedling; Orthophoto; Spectroradiometer; Multispectral Scanner","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":[0.0005311324,0.0001116371,0.000201754,0.00007204359,0.000102195,0.00005698483,0.0002793581,0.00007799799,5.450838e-7],"category_scores_gemma":[0.0004429393,0.0001156723,0.0000313997,0.0003602243,0.0000307667,0.0001068131,0.0001477747,0.0001097383,7.053039e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006499479,"about_ca_system_score_gemma":0.0001896978,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02870132,"about_ca_topic_score_gemma":0.3396198,"domain_scores_codex":[0.9988852,0.00003875756,0.0003946469,0.000304424,0.0001753514,0.0002015766],"domain_scores_gemma":[0.9991985,0.0002740518,0.0001530925,0.0001731649,0.0001713162,0.00002985867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001927129,0.00007761429,0.3663061,0.001275967,0.00009907517,0.00007179931,0.005813686,0.008300964,0.009388163,0.000636626,0.00009388269,0.606009],"study_design_scores_gemma":[0.008124162,0.0003253642,0.158862,0.002389865,0.0001123207,0.00003867308,0.001622064,0.229084,0.5667971,0.03037366,0.001204235,0.001066564],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9518767,0.0001741551,0.0459046,0.00130428,0.0003711124,0.0002443799,0.00000294543,0.00001497062,0.0001068869],"genre_scores_gemma":[0.9941114,0.000003819389,0.005641688,0.00002627175,0.0001017093,0.000001851655,0.00000456042,0.000002076365,0.0001066477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6049424,"threshold_uncertainty_score":0.9777666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02813698727763385,"score_gpt":0.2694585016075483,"score_spread":0.2413215143299144,"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."}}