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Record W6981406631

Eine Radeberger Legende - Max Hinsche (1896 - 1939): Präparator, Großwildjäger, Trapper, Naturwissenschaftler, Schriftsteller

2018· other· de· W6981406631 on OpenAlexaboutno aff

Bibliographic record

VenueQucosa (Saxon State and University Library Dresden) · 2018
Typeother
Languagede
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionTSG101LiquationDysgeusiaFusible alloyHyporeflexia
DOInot available

Abstract

fetched live from OpenAlex

Max Hinsche (* 2.7 1896 Radeberg, † 23.11.1939 Rottenmann/ Steiermark), Präparator, Dermoplastiker, Großwildjäger, Trapper, Naturwissenschaftler und Schriftsteller („Kanada wirklich erlebt“, Erstausgabe 1938, vierte Auflage 2018). Von 1926 bis 1935 begab sich Hinsche im Auftrag der „Staatlichen Museen für Tierkunde und Völkerkunde Dresden“ auf eine 9-jährige Expedition in damals noch relativ unerforschte Gebiete Kanadas (Alberta und Yukon Territory), um seltene und bisher unbekannte Säugetiere und Vögel zu sammeln und zu präparieren. Seine wissenschaftlich fundierten Berichte und Erlebnisse beschrieb er in seinem Buch Kanada wirklich erlebt. 1936 war er Jagdverwalter in den rumänischen Karpaten und begann dort mit dem Manuskript seines Buches. Seine Berichte sind heute noch von großem Wert und genießen insbesondere bei kanadischen Wissenschaftlern hohes internationales Ansehen, da er nachweisbar der erste Wissenschaftler und Trapper war, der seine Beobachtungen so umfassend und tiefgründig, ohne jegliche Abenteuer-Romantik, niederschrieb. Besonders aktuell wurden seine Berichte und wissenschaftlichen Einschätzungen in letzter Zeit wieder für die Wissenschaftler, wenn es um die anstehende Problematik der Wölfe geht.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.084
Threshold uncertainty score0.280

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0840.020

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.249
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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